We offer a range of PhDs funded by different sources, such as research councils, industries or charities. Here you will work with internationally respected academics, post-doctoral research associates and technicians.
To apply for a funded PhD, please read the advertised project information carefully as requirements will vary between funders. The project information will include information such as funding eligibility, application deadline dates and links to application forms. We will only consider applicants who have a relevant background and meet the funding criteria.
Browse our current PhD opportunities
accordion
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Professor James Taylor and colleagues. Jointly funded by the EPSRC and an industrial partner, this project will explore the application of machine learning and digital twin technologies to the nuclear fuel cycle. The studentship is open to suitable graduates in Engineering, Physics, Mathematics, or a closely related STEM discipline.
Industry 4.0 technologies have the potential to transform nuclear energy production. This PhD focuses on applying advanced data-driven methods to an innovative, integrated dry-route uranium conversion process. Unlike conventional wet methods, this approach reduces environmental impact and production costs by eliminating liquid water from the process.
Although designed for autonomous operation, performance can be influenced by complex chemical reactions and changing environmental conditions that are not fully captured in real time. Quality assessment is currently largely offline, with manual intervention. Early studies using limited datasets have demonstrated that machine learning models can successfully predict uranium dioxide output quality from process signals such as pressures, flow rates, and temperatures.
This project will move substantially beyond existing approaches by exploiting richer datasets to develop a high-fidelity digital twin of the manufacturing process, with the PhD researcher developing novel data-driven modelling and analysis techniques. The goal is to enable real-time monitoring, adaptive control, predictive maintenance, and asset management in an industrial environment.
Your Learning Experience
This PhD offers a unique opportunity to combine cutting-edge research with real industrial impact.
You will develop hands-on expertise in:
Data science and machine learning for complex physical systems
Digital twin development and validation
Nuclear fuel cycle fundamentals
Predictive modelling and uncertainty quantification
Working within a safety-critical industrial setting
The project will begin with familiarisation of existing datasets and models, progressing rapidly to the acquisition, pre-processing, and exploratory modelling of newly collected plant data. You will develop predictive models linking process conditions to product quality, before constructing and validating a digital twin of the full manufacturing process.
Forecasting performance will be evaluated via the industrial partner’s facility, giving you direct exposure to real-world deployment and industrial collaboration. Your training will be supported by structured university provision in nuclear engineering fundamentals, advanced computational and statistical methods, project management, and scientific writing. On-site training, secondments, and close industry engagement will further strengthen your professional development.
In the later stages, you will explore how the developed methodologies can be transferred to other safety-critical processes across the nuclear fuel cycle.
This project offers the chance to work at the intersection of AI, advanced manufacturing, and nuclear energy, contributing to safer, cleaner, and more efficient fuel production while building highly sought-after technical and industrial expertise.
Funding and eligibility
This project will be funded by an IDLA studentship (formerly iCASE) for 4 years. This provides for a tax-free stipend at UKRI rates and university fees at the home (UK) rate. Non-UK students might be eligible for higher fee rates and should discuss this with Professor Taylor. The project also has funding to cover travel to the industry partner and conferences/workshops.
Informal enquiries and how to apply
For informal enquiries, please contact Professor James Taylor (c.taylor@lancaster.ac.uk) or other colleagues involved, including Professor Malcolm Joyce and Dr Xiandong Ma at Lancaster University, or Professor Paul Murray at Strathclyde University (https://www.lancaster.ac.uk/engineering/research/airs-nfm/). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project to Professor James Taylor.
PhD Project Description
The rapidly evolving field of microfluidics, in which fluids are manipulated at a microscopic scale, finds many applications in industries, ranging from the pharmaceutical to the oil industry. Most ubiquitous fluids are non-Newtonian and complex such as paints, blood, inks and personal-care products are just a few examples. It also raises curiosity to understand the behaviour of micro- and nano-particles in confinement and under flow that is widely used in various industrial applications, including drug delivery, cosmetics, food, medical diagnostics, environmental remediation, energy and agro-based industries. The technique of controlled manipulation of colloidal particles using microfluidics as a tool in lab-on-a-chip has unlocked opportunities to overcome many limitations of conventional technologies such as the requirement of multiple preparation steps, long processing times and large sample volumes.
The project aims to develop and optimise innovative strategies to control the motion and spatio-temporal distribution of micro/nano-particles in complex fluids in a microfluidic environment. The candidate will design and fabricate microfluidic devices and characterise the flow/particle interaction through optical microscopy methods. There will be exposure to several experimental techniques for the synthesis and characterisation of functional particles and undertaking proof-of-concept studies to identify prospective applications of the developed microfluidic systems - especially for drug delivery and point-of-care diagnostics.
This is an opportunity for a self-funded student, to start at a standard start date (April, October or January).
Informal enquiries and how to apply
For informal enquiries, please contact Dr Naval Singh (n.singh1@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project to Dr Singh.
About the Project
Overview and background
The extraction of energy from the wind yields the formation of low-speed regions (wakes) behind wind farms (WFs). Wakes are particularly persistent offshore [2], and were recently shown to affect the heat exchange between sea and atmosphere, due to reduced convective heat transfer close to the sea surface [1]. With worldwide offshore wind capacity en-route to achieve 2,000+ GW already by 2050, WF wakes may alter ocean dynamics and marine ecosystems to extents comparable to anthropogenic climate change [2]. Evaluating wakes’ environmental impact credibly requires regional- to mesoscale climate simulations with high-fidelity WF parametrisations at temporal and spatial resolution beyond present supercomputers’ capabilities. Using Graphics Processing Unit (GPU) computing [3], this project will develop the code infrastructure to support these simulations on exascale machines, demonstrating prototype physical investigations using the developed technology.
Methodology
Two community codes for short-to-long term climate modelling are considered: the Weather Research and Forecasting (WRF) model [4], and the Model for Prediction Across Scales (MPAS) [5]. The codes feature similar models of atmospheric physics, but use different numerical methods. WRF uses structured grids with nested domains to increase resolution in WF wake regions, whereas MPAS uses a single unstructured Voronoi grid with controllable local refinement. WRF has state-of-the-art WF parametrisations [6,7] but little GPU work reported; MPAS uses GPU acceleration but has little work reported on WF parametrisation.
This research aims at combining the strengths of both codes to develop a reliable exascale-scalable code for the considered problem. The choice of the baseline code for the project’s core development and demonstrations will follow the teaser projects (TPs) below, which offer hands-on training in climate modelling, wind farm aerodynamics and distributed-memory and GPU parallel computing, and assess the codes’ strengths. Following the TPs, the student will focus on specific topics, e.g. improving the overall code GPU framework or optimising the parallelised WF model in existing GPU framework, depending on the code selected.
The TPs will share one test case, to compare the two codes’ predictive capabilities and computational performance (execution speed) without GPU acceleration. The GPU development work will be performed on Lancaster University’s HEC cluster and the Bede supercomputer [9].
Teaser project 1 (TP1): WRF-based. To investigate and optimise the predictive capabilities of the two WF parametrisations [6,7] in WRF, analyses (TC1) of the North Sea area containing two real WFs [10] will be performed. The capabilities of both models to predict wind turbine (WT) and WF wakes will be optimised using regression methods for the models’ parameters, and lidar and satellite wind speed measurements to steer the optimisation. Measured WT power will also be used in the process, as this parameter is affected by wakes. A second test-case (TC2) without WFs will be used to perform parallel profiling studies of WRF, identifying the code’s computationally most intensive parts and familiarising with its structure. These analyses will identify the code sections that would benefit most from GPU acceleration. TC2 will also be used to cross-compare the predictive capability of WRF and MPAS, assessing it by comparing predicted near-sea surface wind speed maps to measurements from satellites and lidars. Boundary and initial conditions for TC1 and TC2 will be taken from the ERA5 global climate reanalysis [8].
Teaser project 2 (TP2): MPAS-based. First, TC2 will be set up and analysed without GPUs to cross-compare the computational speed and prediction capabilities of wind speed field of MPAS and WRF. Then, more comprehensive TC2-based parametric analyses of the performance of MPAS using different numbers of CPUs and GPUs will be undertaken to study the dependence of the computational performance of the hybrid parallelisation on the CPU and GPU counts, and determine the largest achievable acceleration and the corresponding optimal ratio of GPU and CPU counts - an information paramount for exascale porting. These analyses also enable familiarising with the MPAS structure, knowledge needed to optimally merge wind farm models with the MPAS GPU infrastructure.
TP1 Objectives:
A) Familiarise with WRF: assess predictive capabilities of 3D wind fields with/without WFs; analyse/optimise best suited WF parametrisation: B) Assess computational performance and estimate potential of GPU acceleration.
TP2 Objectives:
A) familiarise with MPAS: assess predictive capabilities of 3D wind fields; investigate performance of hybrid CPU/GPU parallelisation; B) Investigate optimal integration of WF model into GPU framework.
Funding Notes
The Scholarship is part of the ExaGEO Doctoral Training Programme funded by the National Environment Research Council. Further information is available at View Website.
This project is a unique opportunity to join a vibrant research team from Lancaster University, University of Manchester and The Cockcroft Institute at Daresbury Laboratory, Warrington, UK, developing world leading concepts for novel acceleration using laser-generated THz pulse.
In the drive toward the understanding and exploitation of laser generated THz pulses through structures that can mediate the interaction process for the control of electron beam properties, dielectric lined waveguides (DLWs) have emerged as one of the most promising solutions. These structures consist of a metallic waveguide lined internally with thin layers of dielectric and can be designed to enhance the interaction between a strong THz field and relativistic electron bunches. By choosing the appropriate electromagnetic mode, these can be optimised as THz-driven deflecting structures for ultrafast diagnostics and beam manipulation. However, several challenges in the design and optimisation of these structures exist, such as the integration of efficient coupling sections to convert the Gaussian cross section mode typically generated by the external THz source into the correct waveguide mode. This project seeks to progress from previous leading work at Cockcroft in rectangular section THz DLWs for beam manipulation. The aim is to develop novel structures for THz-driven beam deflection that maximise efficiency of external THz pulse coupling into the DLW deflecting mode. The project will include studies of the manufacturing and tuning of these structures, longitudinal and transverse beam dynamics, and experimental characterisation.
The 3.5-year project is expected to start in October 2026. The work is mainly based on numerical computation, using full wave electromagnetic codes such as CST Particle Studio. The work will include the development of prototype structures, their test in a THz bunker and data analysis. We welcome applications from students holding or expected a first or upper second-class degree in physics or electronic engineering or other appropriate qualification. Candidates should have a good understanding of electromagnetic theory. Computational skills are desirable but not essential.
Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project to Dr Letizia and additionally follow the application process detailed .
Funding and eligibility: Upon acceptance of a student, this project will be funded by the Science and Technology Facilities Council for 3.5 years. This consists of a tax free stipend at UKRI rates, university fees at the home (UK) rate, plus support for travel to conferences and workshops. A full package of training and support will be provided by the Cockcroft Institute, and the student will take part in a vibrant accelerator research and education community of over 150 people. Non-UK students will be eligible for higher fee rates and should discuss this with the project supervisor.
How to apply: Apply at the Cockcroft Institute PhD webpage. For full consideration for funded awards, please apply by Jan 31st 2026.
Anticipated Start Date: October 2026 for 3.5 Years
Outmuscling snakebite venoms with protein shakes: saving snakebite victims from wounds and limb loss in the Global South with bodybuilding food supplements
Supervisors: Dr. Timothy Douglas, School of Engineering and Dr. Steven Hall, Department of Biological and Life Sciences
Project description: Snakebites can lead to tissue necrosis and chronic wounds, which in turn leads to limb loss, drastically reduced quality of life, or death. The human and economic burden is great, particularly in the Global South.
There is a pressing need to treat snakebites rapidly in-the-field, delivering drugs to neutralize snake venoms, particularly as victims cannot receive immediate medical treatment.
In this interdisciplinary project linking toxicology, pharmacology and engineering, you will:
Deliver novel cocktails of drugs to neutralize snake venoms to prevent or treat tissue necrosis and wound formation.
Develop hydrogels capable of delivering these drug cocktails which can be applied as a dressing to snakebite wounds immediately. These dressings will be based on bodybuilders’ protein supplements, a low-cost material available in vast quantities.
Test the efficacy of your drug cocktail-loaded hydrogel dressing in wound models.
General eligibility criteria: Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course.
Project specific criteria: The ideal candidate will have an interest in conducting experimental, interdisciplinary work and collaboration with colleagues from different countries. We welcome candidates from any scientific background, be it medical, biological, chemical or engineering!
Studentship funding: A tax-free stipend will be paid at the standard UKRI rate; £20,780 in 2025/26. This is a fully funded studentship of 3.5 years for UK/Home students.
Enquiries: Interested applicants are welcome to get in touch to learn more about the PhD project. Please contact Dr. Timothy Douglas (t.douglas@lancaster.ac.uk) and Dr. Steven Hall (s.r.hall@lancaster.ac.uk) for more information.
You will receive a generic acknowledgement in receipt of successfully sending the application documents.
Please note that only applications submitted as per these instructions will be considered.
Please note that, if English is not your first language, you will be required to provide evidence of your proficiency in English. This evidence is only required if you are offered a funded PhD and is not required as part of this application process.
Interdisciplinary Safe Shared Autonomy for Ageing Care with Humanoid Robots (G1-CARE)
Supervisors: Dr Ziwei Wang (Engineering); Dr Elmira Yadollahi (SCC); Professor James Taylor (Engineering); Professor Plamen Angelov (SCC)
Project description: This PhD will develop and validate a safety-assured shared-autonomy framework for a superstar humanoid robot (Unitree G1) targeted at ageing-care workflows (see Figure). The premise is simple: if humanoids are to be accepted in healthcare environments, they must be able to work safely near people, handle everyday objects reliably, and degrade gracefully when perception or communication is imperfect, without placing an unreasonable cognitive burden on staff. The work will be organised around a small set of clinically relevant, low-risk, high-frequency tasks that map directly to care settings, including safe object handover, item retrieval from shelves/trolleys, tray handling, and rehabilitation session setup (e.g., positioning items, presenting tools, preparing a simple station).
These tasks will be implemented on the real G1, with performance judged against explicit safety and usability criteria. Technically, you will build an end-to-end pipeline:
(1) Practical perception + intent inference for care-like scenes. You will fuse multimodal signals (e.g., arm/hand motion cues, gaze and/or speech) with camera perception to infer target object, grasp choice, timing, and handover intent. Vision-language grounding will be used pragmatically: to link verbal instructions to objects/affordances, surface hazard cues, and provide interpretable feedback to the operator. Critically, you will quantify uncertainty and design gating, so autonomy only escalates when perception is reliable; otherwise, the system falls back to safe, operator-led behaviours.
(2) Skill learning and shared autonomy that staff can actually use. You will collect demonstrations using a natural, contact-free teleoperation interface, learn reusable primitives (reach, grasp, handover, fetch-and-carry, tray handling), and organise them into a compositional skill graph. Where appropriate, policies will be refined in simulation under the same safety constraints before transfer to hardware using domain randomisation/residual learning. The shared-control arbitration will be explicitly risk-aware, with transparent override and predictable behaviour around humans.
(3) Human-centred evidence, not just a demo. You will co-design evaluation protocols with ageing-care stakeholders and assess the system using: contact forces/stability margins, task success/time, learning curves, and standard human factors measures such as NASA-TLX and acceptance ratings, complemented by short qualitative feedback. Ethics, accessibility and data governance will be embedded from the start to make outcomes credible for translation.
Outputs will include a reproducible G1 digital twin + safety layer, multimodal interaction datasets (where appropriate), and a benchmark task suite with evaluation protocols and demonstration videos.
General eligibility criteria: Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course.
Project specific criteria: We welcome applicants from Engineering, Computer Science, Natural Sciences or related disciplines. Essential: strong programming skills (especially Python) and Motivation to work across robotics + AI (hands-on, iterative, experimental). Desirable: experience with ROS2/robot simulation, control, machine learning, perception, or human-centred experimentation. You should be motivated by real-world impact in healthcare and committed to safe, inclusive research practice.
Studentship funding: A tax-free stipend will be paid at the standard UKRI rate; £20,780 in 2025/26. This is a fully funded studentship of 3.5 years for UK/Home students.
Enquiries: Interested applicants are welcome to get in touch to learn more about the PhD project. Please contact Dr Ziwei Wang (z.wang82@lancaster.ac.uk) for more information.
Dates
Deadline for candidate applications: 31st May 2026
Provisional Interview Date: June 2026
Start Date: October 2026
Further reading:
D. Ames, X. Xu, J. W. Grizzle, and P. Tabuada, “Control Barrier Function Based Quadratic Programs for Safety Critical Systems,” IEEE Transactions on Automatic Control, vol. 62, no. 8, pp. 3861–3876, 2017.
D. Argall, S. Chernova, M. Veloso, and B. Browning, “A Survey of Robot Learning from Demonstration,” Robotics and Autonomous Systems, vol. 57, no. 5, pp. 469–483, 2009
G. Billard, S. Calinon, and R. Dillmann, “Learning from Humans,” in Springer Handbook of Robotics (2nd ed.), B. Siciliano and O. Khatib, Eds. Springer, 2016, ch. 74, pp. 1995–2014.
Driess et al., “PaLM-E: An Embodied Multimodal Language Model,” in Proceedings of the 40th International Conference on Machine Learning (ICML), PMLR, vol. 202, pp. 8469–8488, 2023.
Zitkovich et al., “RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control,” in Proceedings of The 7th Conference on Robot Learning (CoRL), PMLR, vol. 229, pp. 2165–2183, 2023.
G. Hoffman, “Evaluating Fluency in Human–Robot Collaboration,” IEEE Transactions on Human-Machine Systems, vol. 49, no. 3, pp. 209–218, 2019.
You will receive a generic acknowledgement in receipt of successfully sending the application documents.
Please note that only applications submitted as per these instructions will be considered.
Please note that, if English is not your first language, you will be required to provide evidence of your proficiency in English. This evidence is only required if you are offered a funded PhD and is not required as part of this application process.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Dr Emmanouil Papaioannou.
The primary aim of this proposal is to develop green technologies for the sustainable manufacture of biodegradable membranes, with tailored characteristics for applications in various membrane-based separations (MeSeP). MeSep are promising technologies in various technological applications, including water purification and the recovery of bioactive molecules from dilute aqueous solutions. However, these processes rely heavily on synthetic polymers, some of which may soon be restricted or banned, such as polyvinylidene difluoride (PVDF). Consequently, the development of alternative materials has become increasingly important. This work will place particular emphasis on the manufacture and performance evaluation of composite membranes produced from bio-renewable polymers, such as starch, cellulose and its derivatives, alginates, polylactic acid (PLA), and mixtures thereof. Recent studies revealed that these biopolymers can be an excellent alternative to traditional thermoplastic membranes used in MeSeP.
The proposed biopolymers are fully bio-based and biodegradable thermoplastic polymers with many outstanding properties including easy processability, good strength and stiffness as well as superior biodegradability. There are renewable material and could be decomposed to water and carbon dioxide. However, each of these materials, when used in isolation, exhibits distinct limitations, such as low flexibility, brittleness, poor thermo-mechanical properties, and slow crystallisation rates, which restrict their wider application. To overcome these disadvantages and retain their biodegradability, studies have been carried out to manufacture blends with biodegradable counterparts, such as poly(butylene succinate), poly(ε-caprolactone), and poly(ethylene oxide) (PEO). As well as to improve membrane performance, polymeric membranes can be modified using a variety of techniques such as copolymerization, grafting, cross-linking, and blending. Among the various modification strategies, polymer blending has attracted significant scientific and industrial interest. It not only delivers the desired physical and mechanical properties for the mixture, but it is also a more cost-effective alternative to the synthesis of novel materials. Consequently, composite membranes with the addition of bio-based modifiers are required to achieve the desired stability and pore size. PLA has already used to produce an ultrafiltration membranesfor water purification and tested with bovine serum albumin (BSA) rejection in literature. By increasing the concentration of PLA to 20% the BSA was retained.
Currently, the use of biopolymers in the fabrication of membranes for various separation applications is expanding rapidly. However, there is still lack of clear understanding among the main parameters that affecting the pore formation and the membrane performance, based on its surface characteristics. Experimentally, these natural polymers will be dissolved or suspended within deionised water, and appropriate bio-renewable cross-linkers, such as citric acid, tannic acid and succinic acid, will be tested before being cast at the desired initial thickness and thermally cured until dryness. The bio-renewable polymers concentration within the initial solution, the cross-linker concentration and the curing time conditions are the main parameters that will be examined for tuning the pore-size control, thus the target molecules rejection. The target will be the production of ultrafiltration membranes with pore size of a few thousand Daltons. The cross-linkers are extremely important, allowing these polymers to be permanently fixed within the membrane structure. Variance of the different initial concentrations of bio-renewables polymers and cross-linkers within the initial suspension will be investigated to understand the relationship between each of these components and the final membrane performance. An appropriate design of experiments (DoE) will clarify the contribution of these main parameters to the final membrane properties and performance.
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Dr Emmanouil Papaioannou (e.papaioannou@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project by the closing date 27/04/2026.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Dr Luigi Capozzi.
Microplastics are now widely recognised as an emerging environmental challenge due to their persistence, widespread distribution, and potential impact on ecosystems and human health. Their effective detection, characterisation, and removal remain significant technical challenges, particularly when dealing with complex liquid streams and small particle sizes.
This PhD project will focus on the development of innovative approaches for the detection and separation of microplastics. The research may include experimental, computational, and design-based activities aimed at improving the identification of microplastic particles and enhancing their removal from relevant process streams. Possible areas of investigation include microfluidic systems, particle transport and separation mechanisms, sensor integration, imaging-based detection, and data-driven analysis.
The student will contribute to the design and testing of new platforms and methodologies for microplastics analysis, with the broader aim of supporting more efficient monitoring and remediation strategies. The project is expected to combine fundamental engineering principles with practical applications in environmental and process engineering.
Supervisory Team:
- Dr Luigi Capozzi (Lead supervisor, School of Engineering, Lancaster University)
- Dr John Hardy (co-supervisor, Chemistry department, Lancaster University)
The research will be conducted in collaboration with Dr. Mariacristina Cocca at the Institute of Polymers, Composites and Biomaterials (IPCB-CNR, Naples).
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Dr. Luigi Capozzi (l.capozzi@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project by the closing date 27/04/2026.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Dr Lei Wang.
Overview
The transition toward sixth-generation (6G) wireless networks and advanced Space systems is driving the need for more efficient and intelligent radio technologies. A key emerging concept is Integrated Sensing and Communication (ISAC), which enables wireless systems to simultaneously perform data transmission and environmental sensing using shared spectrum, hardware, and waveforms. This paradigm eliminates the need for separate infrastructures and supports a wide range of applications, including smart homes, indoor monitoring, human activity recognition, and intelligent Space systems.
The importance of ISAC is highlighted by ongoing standardisation activities. The ETSI has defined key ISAC use cases and architectures, while 3GPP Release-19 introduces sensing-enabled services and associated performance metrics such as accuracy, latency, and reliability. These developments reflect a growing demand for multifunctional and resource-efficient wireless systems.
However, current solutions typically rely on multiple separate devices for communication, sensing, and wireless power transfer, resulting in increased cost, complexity, and energy consumption. This project aims to address these challenges by developing a single, intelligent antenna platform capable of supporting all three functionalities.
Project Description
This PhD project will investigate leaky-wave antennas (LWAs) and arrays as a unified hardware platform for integrated sensing, communication, and wireless power transfer. LWAs offer unique advantages due to their inherent frequency-dependent beam-scanning capability, enabling dynamic spatial coverage without complex beamforming networks.
The project will progress through four stages, starting with the design of advanced and innovative leaky-wave antennas and arrays with improved beam-scanning performance. It will then develop a millimetre-wave sensing platform for applications such as direction finding and motion detection. Building on this, the research will integrate sensing and communication within a unified antenna system aligned with emerging 6G standards. Finally, it will extend the platform to support simultaneous wireless information and power transfer, culminating in a fully integrated, experimentally validated multifunctional system.
Research Approach
This project combines theory, simulation, and hands-on experimental work. You will:
Design and optimise antenna structures using full-wave electromagnetic simulation tools
Fabricate and test antenna prototypes using advanced measurement facilities
Develop system-level prototypes using software-defined radios and mmWave hardware
Experimentally evaluate performance across communication, sensing, and power transfer domains
Analyse trade-offs between system functionalities and optimise overall performance
Research Environment
The project will be hosted by the Antenna and Sensing Group in the School of Engineering at Lancaster University.
You will have access to state-of-the-art facilities, including:
A newly established anechoic chamber (0.6–40 GHz) with near- and far-field measurement capabilities
A sub-terahertz near-field scanner (75–140 GHz)
5G Ka-band, W-band, and D-band up/down converters
Software-defined radios for rapid prototyping
A 5G Ka-band digital beamforming platform
High-performance workstations with GPU acceleration
Full-wave simulation software
This environment provides an excellent opportunity to gain both theoretical knowledge and practical skills in cutting-edge RF and wireless systems research.
Expected Outcomes
This project will deliver:
Novel leaky-wave antenna and array designs with improved beam-scanning performance
A fully functional mmWave sensing platform
Integrated ISAC system prototypes aligned with emerging 6G standards
A SWIPT-enabled multifunctional wireless system
Multiple high-quality publications in leading IEEE journals and conferences
The research will contribute to future smart connectivity solutions with applications in smart homes, healthcare, autonomous systems, and Space technologies.
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Dr Lei Wang (lei.wang@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project by the closing date 27/04/2026.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Prof Raffaella Villa.
We are seeking an enthusiastic and motivated PhD researcher to join an exciting project exploring fungal biotechnology as a breakthrough solution for natural textile waste degradation and enzyme production. This fully funded doctoral project offers you the opportunity to work at the intersection of environmental science, microbiology, industrial biotechnology, and materials sustainability, contributing to a new generation of low-energy, bio-based methods for textile valorisation.
The global fashion and textile industry is often cited among the most environmentally damaging sectors worldwide. Across the entire value chain, from raw material cultivation and fibre processing to dyeing, garment finishing, and disposal, textile production places an enormous burden on ecosystems, natural resources, and waste streams. One of the biggest challenges is the complexity of textile waste itself. Materials are made from diverse natural and synthetic fibres, blended compositions, and chemical additives (such as dyes, finishes, and fire retardants). These factors complicate sorting, recycling, and recovery, leading to huge volumes of textiles being landfilled or incinerated each year.
While researchers have made progress in chemically breaking down and upcycling waste textiles into valuable new products, many of these technologies remain energy‑intensive, chemically aggressive, and costly, limiting their real‑world implementation.
There is a pressing need for innovative, biologically driven, low‑cost, and sustainable alternatives. Fungi are remarkable organisms capable of degrading a huge variety of organic substrates. Species such as Aspergillus niger have already demonstrated powerful abilities to break down lignocellulose-rich materials, including agricultural residues, cotton, and hemp. Their enzymatic pool allows them to degrade complex polymers efficiently and with minimal environmental impact. Surprisingly, however, very little research has explored the potential of fungi to degrade protein‑rich textiles such as wool and silk. Keratin, the tough fibrous protein that makes wool resistant to mechanical and environmental wear, presents a difficult challenge but also a great opportunity. In other contexts, fungal keratinases have been successfully used to degrade feather waste, which is chemically similar to wool. This suggests that fungal systems may hold the key to unlocking sustainable wool breakdown and valorisation.
The overarching goal of this doctoral research is to evaluate and optimise the ability of fungi to degrade natural textile fibres, focusing specifically on wool‑based materials. The student will contribute to the design and testing of new methodologies for fungal growth on textile waste, with the broader aim of producing multiple high-value by-products such as enzymes.
By joining this project, you will become part of a supportive research environment with expertise in environmental biotechnology, mycology, enzyme science, and sustainable materials processing. You will gain:
· Laboratory training in microbiology and fungal cultivation
· Experience with solid-state fermentation and bioprocess optimisation
· Skills in analytical chemistry and materials characterisation
· Insights into sustainable waste management and circular economy strategies
· Opportunities to publish your work in high-impact journals
· Professional development in scientific communication, presentations, and collaboration
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Prof Raffaella Villa (r.villa@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project by the closing date 27/04/2026.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Dr Peter Carrington.
There is great worldwide interest in the development of light emitting diodes (LEDs) and lasers operating in the mid-infrared spectral range (2-5 µm) because it offers many potential applications in a variety of areas. For example, it contains the absorption bands of a number of pollutant and toxic gases including methane (3.3 µm), CO2 (4.25 μm), CO (4.73 μm) and SO2 (4.0 μm) which require accurate, in situ multi-component monitoring in a variety of different situations (e.g. oil-rigs, landfill sites, power stations, car exhausts). There are also potential medical applications since many biological molecules absorb and radiate in this spectral range. In addition, there is an atmospheric transmission window between 3.6 and 3.8 μm which enables free space optical communications and thermal imaging applications in both civil and military situations as well as the development of infrared countermeasures for homeland security. However, the development of instrumentation is currently limited by the availability of efficient and affordable light sources and detectors.
The aim of this project is to explore new mid-infrared semiconductor materials to enhance the quantum efficiency which will vastly improve the device performance. The project is intellectually challenging and involves well-integrated elements of electrical engineering, physics and materials science. The successful applicant will learn a wide range of skills including device fabrication, experimental characterisation and semiconductor modelling. The work will also be carried out in close collaboration with leading international research groups and industries.
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Applicants would normally be expected to hold a minimum of a UK Honours degree at 2:1 level or equivalent in a relevant degree course. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Dr. Peter Carrington (p.carrington@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project by the closing date 27/04/2026.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University, supervised by Dr Peter Carrington and Dr Rob Apsimon.
In this project, we will take an interdisciplinary approach to fight cancer, combining biomaterials derived from the dairy industry and multifunctional electron beam technology to create treatments for gastrointestinal and skin cancers, combine the expertise of Lancaster University and the Cockcroft Institute in Daresbury.
Gastrointestinal cancers and skin cancers are major problems in the UK and worldwide: colonic cancer is the most common cancer among women. There is a demand for biomaterials which can serve as drug delivery vehicles for anticancer drugs. Localised, targeted delivery decreases the systematic side effects on the rest of the body and reduces the overall amount of drug needed.
From a biomedical perspective, such biomaterials should be cytocompatible (harmless to cells) and able to encapsulate a wide range of drugs, and easily sterilized, a prerequisite for applications in medicine. From a materials science perspective, they should have appropriate physiochemical properties, such as mechanical integrity and the ability to release drugs at an appropriate rate. Furthermore, from a chemical/process engineering perspective, the biomaterials should have practical characteristics enabling easy upscaling of production; they should be cheap, available in large quantities, and safe to produce.
Whey Protein Isolate (WPI) is an inexpensive by product of the dairy industry available in large quantities and marketed as a protein supplement for bodybuilders. Importantly, WPI solutions form hydrogels, or 3D polymer networks containing entrapped water, when heated. In our numerous previous publications on WPI hydrogels, we have demonstrated that WPI is harmless to cells and can incorporate a wide range of biomolecules, both hydrophilic and hydrophobic, and can serve as a delivery vehicle for molecules which inhibit colon cancer cell growth.
Novel electron beam treatment, available at Daresbury Laboratory, can polymerise WPI solutions to make hydrogels. The use of electron beam crosslinking has several advantages including that the irradiation process produces minimal heating, which is a significant advantage on temperature-sensitive drugs, whereby the standard formation process for hydrogels is to heat it up.
The successful student will be able to attend a full accelerator training programme at the Cockcroft Institute in Daresbury during their first year. During this time, the student will learn about methods of forming hydrogels as well as the fundamentals of particle interactions with matter.
In the second year, the student will undertake a full simulation study in GEANT4 to understand how the electron beam interacts with the drugs and the hydrogels. In addition the student will undertake tests in the lab on hydrogels, analysing the chemical composition, as well as the chemical and physical properties of the hydrogel, such as dose delivery rate.
In the third year, we anticipate the student undertaking beam tests at Daresbury Laboratory, which will involve planning the tests, preparing samples for irradiation and analysing the samples after testing and taking leadership of the testing stage. The student is expected to then write up and submit their thesis within 3.5 years.
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Candidates from an engineering, natural science or medical background with an interest in multidisciplinary work in international research groups are encouraged to apply! A 2:1 or equivalent in their first degree is required for this position. We encourage candidates from all ethnic backgrounds to apply.
For informal enquiries, please contact Dr. Tim Douglas (t.douglas@lancaster.ac.uk) and Dr. Rob Apsimon (r.apsimon@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project by the closing date 27/04/2026.
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University (LU), supervised by Dr Sergio Campobasso and Prof James Taylor. Jointly funded by EPSRC and supported by a partnered international research network [7], this multi-disciplinary project will develop and optimise a new wind turbine control method, sensing and reacting to meteorological conditions, and aiming to minimise blade erosion and maximise wind turbine energy yield. The studentship is open to suitable graduates in Engineering, Physics, Mathematics, or a closely related STEM discipline.
The ongoing growth of turbine blade length (presently 100+ m) and tip speed (presently 100+ m/s) are exacerbating blade leading edge erosion (LEE) [6] due to repeated high-speed collisions of blades and rain droplets and/or hailstones. The resulting surface degradation reduces the aerodynamic performance of the blades, yielding notable power and Annual Energy Production (AEP) losses [3]. Repairing LEE damage increases Operation and Maintenance (O&M) frequency and costs, particularly high in offshore operation. Reducing overall AEP losses and O&M costs to accelerate offshore wind growth is the main aim of this PhD project.
The research will contribute to investigating and bringing closer to field deployment the atmospheric Precipitation-Reactive Control (PRC) concept [2], a turbine control method aiming to minimise LEE of fixed-bottom and floating offshore wind turbines (FBWTs & FOWTs). In the more general FOWT case, PRC-enabled turbine operation aims to optimise power and loads and ensure platform stability whilst also mitigating LEE by curtailing rotor speed during erosive precipitation events according to carefully designed strategies.
For the first time, this PhD project will:
A) investigate and optimise multi-level PRC operation strategies, using machine learning-accelerated optimisation to determine the PRC wind speed and rainfall rate activation thresholds that optimise the trade-off of blade maintenance frequency, LEE-induced AEP loss and AEP loss due to speed curtailment;
B) explore and assess a real-world implementation of PRC for both FBWTs and FOWTs, with the aim of identifying and resolving presently unknown operational constraints, particularly in the case of FOWTs, in which sudden changes of rotor speed and blade pitch may compromise stability and structural integrity of the floating system.
Your Learning Experience
This PhD offers a unique opportunity to combine cutting-edge research with real industrial impact.
You will receive training and develop hands-on expertise in:
• Digital twin development and validation
• Foundations of fixed-bottom and floating turbine control, aerodynamics and wave-structure interaction
• Foundations of control engineering and computer programming
• Machine learning for problem dimensionality reduction, multi-objective optimisation and uncertainty analysis
• Working within an international team of industrial and academic researchers
The project will begin with familiarisation with the foundations of PRC [2], and the meteorological datasets and LEE analysis methods [4] needed for progressing PRC and moving towards field deployment. You will then explore PRC generalisations for improved performance adopting multiple levels of speed curtailment, a task investigated with multi-disciplinary numerical optimisation and measured long-term time-series of meteorological data at existing and forthcoming wind farm sites, with uncertainty analysis used to assess result sensitivity to possible inaccuracies of data and models. The onshore sites will include Lancaster Hazelrigg, hosting LU’s 2.3 MW turbine and a UK Met Office weather station, and an existing digital twin of this turbine will be refined and used in the project. The offshore sites will include two North Sea sites, one of which hosts a large Orsted wind farm. In all cases, machine learning will be used for rapid assessment of AEP losses due to LEE [3].
The outcome of the first part of the research will provide the values of the precipitation parameters (e.g. rainfall rate) for each speed curtailment level to achieve optimal trade-offs of blade longevity and AEP based on asymptotic (i.e. steady) control, power and load curves. To determine possible additional constraints requiring alterations of the underlying baseline turbine control, you will then implement PRC in a real-world wind turbine control, e.g. the ROSCO toolkit [1,5] of the National Laboratory at the Rockies (previously called NREL). To pave the way to field deployment, the ROSCO-PRC controller will be used to investigate and resolve possible critical states, yielding excessive unsteady loads and/or FOWT loss of stability, due to sudden PRC-induced variations of turbine operation (i.e. overly fast variations of rotor speed and/or blade pitch). The potentially critical operations will be extracted from the optimised states determined in the first part of the project.
Your training will be supported by structured university provision in fundamentals of renewable energy systems, advanced computational and statistical methods, project management, and scientific writing. On-site training, secondments, and close industry engagement will further strengthen your professional development.
This project offers the chance to work at the intersection of wind energy, data science and mathematical modelling and multi-disciplinary optimisation including uncertainty, to accelerate offshore wind growth and increase infrastructure resilience to climate change (more frequent and intense precipitation), while building highly sought-after technical and industrial expertise.
Funding Notes
This project is funded by UKRI/EPSRC. The funding covers the cost of the tuition fee for UK students and a standard tax-free EPSRC stipend for 3.5 years for UK applicants.
Non-UK candidates are welcome to apply. If successful, they will have to pay the difference between overseas tuition fees and UK tuition fees, which is NOT provided by this Scholarship.
The successful candidate should preferably start in October 2026.
Eligibility criteria
Candidates from an Engineering, Physics, Mathematics, or a closely related STEM discipline. A 2:1 or equivalent in their first degree is required for this position. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Dr Sergio Campobasso (m.s.campobasso@lancaster.ac.uk) or Prof. James Taylor (c.taylor@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project to Dr Sergio Campobasso.
References
1. N.J. Abbas, D.S. Zalkind, L. Pao, A. Wright, A reference open-source controller for fixed and floating offshore wind turbines, 2022, Wind Energy Science, 7(1). 2. M.S. Campobasso, M.S. Rose, S. Shende, E. Adirosi, G. Pace, L. De Silvestri, K. Dimitriadou, A. Vinod, C. Bay Hassagere, F. Sanchezf, A. Castorrini, Development, performance and energy trade-off analyses of wind turbine precipitation-reactive control at offshore and onshore sites in Western Europe, 2025, Renewable Energy, under review. 3. L. Cappugi, A. Castorrini, A. Bonfiglioli, E. Minisci, M.S. Campobasso, Machine learning-enabled prediction of wind turbine energy yield losses due to general blade leading edge erosion, 2021, Energy Convers. Manag., 245, 114567. 4. A. Castorrini V.F. Barnabei, L. Domenech, A. Sakalyte, F. Sanchez, M.S. Campobasso, Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades, 2024, Renew. Energy, 227, 120549. 5. NREL, Reference OpenSource Controller (ROSCO) toolbox for wind turbine applications, https://github.com/NatLabRockies/ROSCO accessed on 20/3/2026. 6. S.C. Pryor, R.X. Barthelmie, J.J. Coburn, X. Zhou, M. Rodgers, H. Norton, M.S. Campobasso, B. Mendez-Lopez, C. Bay Hassager, L. Mishnaevsky Jr, Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions, 2024, Energies, 17(24): 6285. 7. International Energy Agency – Wind Division, Task 46: Erosion of Wind Turbine Blades. https://iea-wind.org/task46/
About the Project
Applications are invited for a fully funded PhD studentship (UK fees and stipend) in the School of Engineering at Lancaster University (LU), supervised by Dr Basu Saha and Dr Amos Dexter.
Background and project description
Commercial, domestic, and educational activities generate diverse waste streams that are typically classified as recyclable, compostable, or non-recyclable. Currently, most non-recyclable waste is sent to landfill or incineration, incurring high gate fees and, in some cases, environmental risk. A more sustainable waste-management strategy would introduce a fourth category: waste suitable for gasification. This includes contaminated food packaging, coffee grounds, medical wastes, polystyrene, and mixed non-fluorinated plastics with fillers or pigments - materials that are difficult to recycle and are landfilled in significant quantities, including at Lancaster University. Reducing landfill disposal and associated greenhouse-gas emissions is therefore a key sustainability priority.
Gasification converts such waste into synthesis gas (syngas), which can be stored and subsequently used to generate electricity via high-efficiency gas turbines. Microwave plasma gasification, in particular, employs electricity to achieve very high operating temperatures, minimising char formation and maximising energy recovery. As the UK electricity system becomes increasingly dominated by wind and solar generation, plasma gasification offers a unique demand-side management opportunity: waste can be processed when electricity prices are low, while syngas can be stored and utilised when electricity demand and prices are high.
Lancaster University School of Engineering has been collaborating with an industrial partner, Stopford Energy, since 2017 to develop plasma gasification of organic waste. A facility has been progressively established in the university with microwave equipment, gas supplies, gas extraction and analysis equipment. The research was carried out primarily by two former PhD students, who graduated in 2020 and 2025. Since 2024, Lancaster University has developed a new applicator technology that gives higher efficiency and throughput.
Through this project, we aim to strengthen our research focus on plasma chemistry, gasification, and renewable energy. Stopford Energy will provide in-kind support by participating in project meetings and offering guidance to help ensure the success of the proposed PhD programme. The ongoing UKRI APP7279 project primarily focuses on technology development. Integrating a PhD studentship alongside this effort adds value by enabling a more in-depth investigation of the science, ultimately enhancing the quality of research outputs. Through engagement with Stopford Energy, the PhD student will accelerate knowledge transfer, strengthen technical leadership in advanced thermal conversion, and support scalable, commercially viable waste-to-energy solutions aligned with net-zero and circular economy goals.
PhD project and topics for investigation
The PhD project will undertake a scientific investigation of the plasma and associated gas-phase chemistry to deepen our understanding and enable high-quality research publications. The PhD project will solve issues of syngas cleanup dependent on the feedstock to the gasifier.
The PhD student will undertake the following activities:
· Plasma measurements, including analysis of spectra.
· Chemical analysis of input and output streams.
· Modelling of the plasma and associated gas flows, including chemical reactions.
· Optimisation of process parameters:
Ø maximising conversion;
Ø minimising harmful emissions;
Ø minimising any need for subsequent processing.
Social and economic impact
As fossil fuel use declines to mitigate climate change, the generation of organic waste from agriculture, forestry, and chemical processing is expected to remain constant or increase. Preventing this waste from decomposing into high-global-warming-potential gases such as methane is critical. Maximising energy recovery from organic waste, therefore, represents a key pathway toward achieving net-zero emissions.
The proposed plasma gasification technology offers significant environmental, social, and economic benefits by enabling the treatment of thousands of tonnes of organic waste annually in the UK, while delivering higher energy recovery and substantially lower greenhouse-gas emissions than existing technologies. By converting waste into usable energy and stable by-products, the process supports energy security, reduces landfill dependency, and promotes a circular economy. Economically, the technology offers reduced regulatory and compliance costs compared to conventional incineration, as emissions are limited primarily to CO₂, water vapour, and a small fraction of inert vitrified slag. This improves commercial viability and investor confidence. Overall, the project supports national and international climate commitments and aligns strongly withUN Sustainable Development Goals 12 (Responsible Consumption and Production) and 13 (Climate Action).
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
A 2:1 or equivalent in their first degree is required for this position. We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For informal enquiries, please contact Dr Basu Saha (b.saha@lancaster.ac.uk) or Dr Amos Dexter (a.dexter@lancaster.ac.uk). Candidates interested in applying should send a copy of their CV together with a personal statement/covering letter addressing their background and suitability for this project to Dr Basu Saha.
References
[1] Vecten, S., Wilkinson, M., Martin, A., Dexter, A., Bimbo, N., Dawson, R., Herbert, B., Experimental study of steam and carbon dioxide microwave plasma for advanced thermal treatment application, Energy, 2020, 207, 118086 (1-9), https://doi.org/10.1016/j.energy.2020.118086. [2] Duong, L., Dexter, A., Wilkinson, M., Saha, B., Scale-up applicator for microwave plasma gasification, 33rd European Biomass Conference and Exhibition (EUBCE) 2025, Valencia, Spain, June 2025. [3] Chooyin, J., Dexter, A., Duong, L., Steventon, A., Saha, B., Sustainable valorisation of tyre crumb via microwave-induced plasma gasification, International Conference on the Expanding Horizon of Chemical Engineering, Kolkata, India, December 2025.
About the Project
A fully funded PhD studentship is available for a motivated candidate to undertake advanced applied research in the development of lab-on-chip systems to investigate carrier transport, behaviour and interactions in controlled microfluidic environments for healthcare technologies. You will be a member of a vibrant research group with state-of-the-art microfabrication facilities and will receive full support and training to develop your research skills. During the project, you will collaborate with multidisciplinary researchers from University College London and Institute Lumière Matière at the University Claude Bernard Lyon 1.
Background
The future of healthcare technology depends on innovative experimental platforms that are robust, versatile and capable of high-resolution analysis. Microfluidic and lab-on-chip systems are driving major advances in this rapidly evolving area, creating exciting opportunities for precision-engineered research tools and next-generation healthcare applications. These technologies are becoming increasingly important in complex biomedical settings, where there is growing demand for advanced platforms that can support new approaches to investigation, testing and device development. By enabling highly controlled and adaptable microscale environments, microfluidic approaches offer significant promise across a wide range of translational and emerging applications. This PhD project provides an exciting opportunity to contribute to cutting-edge research at the interface of engineering and healthcare.
Aim of the project
This project aims to develop and investigate innovative functional carrier systems using advanced lab-on-chip platforms, with a focus on controlling their behaviour in complex microscale environments. The successful candidate will design and fabricate microfluidic devices, establish experimental microsystems, and use optical and fluorescence microscopy to study system interactions and performance. The project will provide interdisciplinary training in microfabrication, particle synthesis and characterisation, and proof-of-concept studies to explore the broader potential of the developed microfluidic platforms in future healthcare applications.
Funding Notes
This PhD studentship is fully funded for 3.5 years for Home (UK) students. It consists of a tax free stipend at UKRI rates (£20,780 for the 2025/26 academic year, with annual increments subject to UKRI adjustments) and University fees at the Home (UK) rate. The studentship is open to both UK and international applicants, with a start date of October 2026. International applicants are eligible for higher fee rates and, if successful, will be required to fund the difference in fees.
Eligibility criteria
Candidate will have, or expect to have, a UK Honours Degree (or equivalent overseas degree) at 2.1 or above in Chemical/ Mechanical/ Materials Science and Engineering, Chemistry, Biochemistry, Physics, or related discipline.
Experience in any of the listed areas - Microfluidics/Microfabrication, colloidal and interface science, surface chemistry, polymers, rheology, and data analysis/modelling are desirable although not a requisite.
Good oral and written communication skills with the ability to prepare presentations, reports, and journal papers. Overseas applicants should submit IELTS results (minimum 6.5) if applicable.
We encourage candidates from all ethnic backgrounds to apply.
Informal enquiries and how to apply
For any informal enquiries or more information about this position, candidates are encouraged to contact Dr Naval Singh n.singh1@lancaster.ac.uk. Candidates interested in applying should send a copy of their CV and a personal statement/covering letter addressing their background and suitability for this project to Dr Singh.
References
N. Singh et al., Physical Review Letters, 125, 24, 248002 (2020) N. Singh et al., Langmuir, 38, 46, 14053–1406 (2022)
SATURN-CDT PhDs
The EPSRC Centre for Doctoral Training (CDT) in Skills And Training Underpinning a Renaissance in Nuclear (SATURN) is a collaborative CDT involving the Universities of Manchester, Lancaster, Leeds, Liverpool, Sheffield and Strathclyde will work towards building the skills base needed to support the UK’s net zero targets. Please see the listed Lancaster-based PhD opportunities below:
How to apply
Step 1
To register your interest in a PhD opportunity, please email the relevant project supervisor with your contact details and a comprehensive CV. Please also include a covering letter, if requested in the advert details.
Step 2
The project supervisor will contact you and may invite you to hold a Skype or telephone interview. At this stage, you can apply for more than one advertised project if you wish.
Step 3
If you are successful at interview for the studentship, you will be invited to apply via the admissions portal online. This will ensure that you receive a formal offer of admission. Please submit one application only, and state the studentship that you have applied for in the source of funding section.
Step 4
Once we have made a formal offer, you will need to check the conditions in your offer letter and supply any outstanding documents by the required deadlines. If your offer is unconditional, then this will not apply to you.
Other methods of applying for a PhD
Studying for a research degree is a highly rewarding and challenging process. You'll work to become a leading expert in your topic area with regular contact and close individual supervision with your supervisor.
If you have your own research idea, we can help you to develop it. To begin this process you will need to find a PhD Supervisor from one of our research groups, whose research interests align with your own.
