Newcastle University, England invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at Newcastle University, England.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentships in Statistics, Data Science and Machine Learning
We are offering three funded PhD studentships. Available PhD projects include (detailed project descriptions and supervisor contact details can be found here):
- Digital twins with state-of-the-art Gaussian process emulation for decision making under uncertainty (Studentship code MSP106)
- Learning to sample: Meta-optimisation of gradient flows using reinforcement learning (Studentship code MSP107)
- Dynamic Bayesian modelling of endurance sports (Studentship code MSP108)
- Data structures and postprocessing for phylogenetic MCMC (Studentship code MSP109)
- Time-changed MCMC for complex sampling (Studentship code MSP110)
- Statistical learning for extreme values with application in finance and risk management (Studentship code MSP111)
- Bayesian additive regression trees and genetics data (Studentship code MSP112)
Deadline : 2nd February 2026
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship: Visual Prosthesis for the Blind
This PhD is an opportunity to take part in research into advanced neuroprosthetic solutions to bringing sight back to the blind (i.e. bionic vision). The Newcastle Visual Prosthesis project is developing a special brain implant which works in tandem with gene therapy to stimulate the visual cortex and thus bypass the broken elements of the visual system in various blinding disorders.
Our implant combines photonics, microelectronics, embedded systems, advanced implant probe design and signal processing. There are opportunities for students from a variety of backgrounds to work on the following possible projects:
- Bionic Vision microelectronics: In this project, you would develop advanced low-power mixed-signal (analog + digital) circuitry on CMOS chips which will drive our custom implants
- Bionic Vision implantable probes: In this project, you will use advanced microfabrication (cleanroom) techniques to combine electronics, photonics, and biocompatible brain probes.
- Bionic Vision Embedded Systems: Here, you would combine advanced microcontrollers, power and data transmission systems to create a subcutaneous control unit for bionic vision.
- Bionic Vision Biophysics: Here, you will explore the basic biophysics/neuroscience issues that have been a barrier to bionic vision to date, then develop advanced methods to talk to the brain.
Deadline : 18th February 2026
View All Fully Funded PhD Positions Click Here
(03) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship: Teaching Intelligent Agents to See, Think and Act with Vision and Language
How can we revolutionise intelligent systems that still rely on fixed rules and structured commands?
For example, if asked to “pick up the red book on the shelf,” a traditional robot would need the exact location and object details programmed in advance. If anything changes, it may fail.
This project explores how to build more adaptable systems using vision-language-action (VLA) models. These combine computer vision (to see), natural language understanding (to interpret instructions), and action generation (to respond), enabling robots to perceive, reason and act flexibly.
The models will be trained on simulated datasets to learn general behaviours, then fine-tuned for specific tasks. The aim is to create intelligent agents that could demonstrate human-like understanding and adaptability if applied to real-world scenarios.
Deadline : 18th February 2026
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship: Structural and Material Influence on Floor Vibration-Based Fall Detection
Falls are one of the most serious safety risks for older adults, and rapid, reliable detection can significantly reduce long-term injury and improve emergency response. Building on recent advances in vibration-based sensing, this PhD will explore how the structural and material characteristics of floor systems influence the vibration signatures produced by human falls and other everyday activities.
While existing research often assumes a single, uniform floor condition, real buildings vary widely, from timber and composite systems to reinforced concrete slabs, each with unique stiffness, damping, and boundary conditions. These structural differences fundamentally shape how vibration signals are transmitted and recorded. This project will therefore investigate how these variations affect signal detectability and classification performance of AI models for fall detection.
The research will combine experimental studies on different floor systems, finite element simulations of vibration propagation, and AI-based signal analysis to establish a physics-informed understanding of the relationship between structural behaviour and fall detection accuracy.
Deadline : 18th February 2026
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship: Engineering Bioinstructive Materials to Guide Immune–Bone Regeneration
Bone regeneration relies on more than bone growth; it depends on a complex dialogue between immune and skeletal cells. When this communication falters, healing slows or fails. This PhD will explore how mechanical and topographical cues such as stiffness, nano-roughness, and viscoelasticity govern immune–bone interactions through mechanotransduction pathways.
The goal is to design bio-instructive materials that actively direct immune and bone cells toward regeneration. These will be characterised using AFM and rheology, followed by immune–osteogenic co-culture studies to evaluate mechanotransductive signalling. The resulting data will inform mathematical models linking material mechanics to biological responses, enabling the sustainable design of next-generation regenerative materials.
This interdisciplinary project combines mechanical, materials, and biomedical engineering, offering training across fabrication, nanomechanical analysis, and computational biology. It contributes to more predictive and reproducible approaches in regenerative medicine, reducing reliance on animal models and advancing mechanobiology-informed materials design.
Deadline : 18th February 2026
Polite Follow-Up Email to Professor : When and How You should Write
Click here to know “How to write a Postdoc Job Application or Email”
(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship: Development of a robust hydrological modelling framework for drought risk assessments
Globally, drought and water scarce events pose a significant threat to water security, resulting in catastrophic direct and indirect impacts across domestic and water-intensive sectors such as agriculture, power generation, and manufacturing (OECD, 2025). Regions across England face critical water security challenges due to high population density, intensive agriculture, and shifts in climate towards drier summers and higher variability in rainfall (CCC, 2019). Without adaptation and investment, water availability is projected to fall short of meeting future demands, with supply-demand deficits becoming widespread by the 2050s.
To effectively plan for water supply resilience, it is essential to robustly model future changes in hydrological systems. This project will develop a robust modelling framework to simulate future changes in water resources in North and East England, using a combination of physically-based hydrological modelling tools and water system models. The framework will be used to produce more transparent and physically realistic projections of water resource availability under extreme climate and demand scenarios for the region.
Deadline : 30 January 2026
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship: Autonomous robotics for enhanced water management, natural processes and resilience.
Nature-based Solutions (N-bS) are increasingly recognized as effective strategies for addressing global challenges linked to climate change. By enhancing landscape systems, N-bS strengthen resilience, improve ecosystem health, and secure water availability. Their form varies with local conditions but often includes river and wetland restoration, distributed storage and recharge ponds, afforestation and reforestation, and shifts in land use or management practices. Although awareness and adoption of N-bS are growing, greater efforts are required to accelerate interventions capable of counteracting current and emerging climate threats.
Autonomous robotics and associated digital systems are advancing rapidly across terrestrial, airborne, and aquatic platforms. Robotics are becoming more versatile, capable of operating in difficult environments with increasing autonomy. This creates significant opportunities to deploy robotics in support of N-bS, helping mitigate climate impacts while benefiting both society and the environment.
This research will explore how robotics are applied in sectors such as construction, manufacturing, and defence, and assess how related technologies could be adapted to implement N-bS. Proof of concept will be developed through laboratory and field experiments, demonstrating robotics in tasks such as planting, building, and environmental management.
Deadline : 28.02.2026
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship: Adaptive Logic-Based Machine Learning Grids
This project will develop an adaptable Machine Learning (ML) hardware architecture to solve Artificial Intelligence (AI) classification tasks using Internet of Things (IoT) sensor data. This will be a small system-on-chip designed to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware compared to the current state-of-the-art. The project will align the in-house algorithm-to-hardware development of the Micro-Systems Research Group at Newcastle University with next-generation Field Programmable Gate Array (FPGA) hardware technologies i.e. OpenFPGA.
Deadline : 18th February 2026
Click here to know “How to Write an Effective Cover Letter”
(09) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Trustworthy Multimodal AI under Lightweight and Data-Efficient Architectures
Multimodal artificial intelligence (AI), which integrates diverse information sources including tabular, imagery, linguistic and acoustic data, has shown transformative potential in domains such as healthcare, environmental monitoring, and autonomous systems. However, most advances rely on large datasets and computationally intensive architectures that are impractical for scenarios constrained by limited data and resources for fine-tuning and deployment of large-scale models. What’s more, multimodal models are particularly vulnerable to data uncertainty, modality dropout, and noise propagation, which can degrade robustness and erode trust in model outcomes. This project aims to create a unified framework for building lightweight, data-efficient multi-modal AI models that can effectively handle uncertainty and generate reliable outputs.
This is an exciting opportunity to work at the cutting edge of AI research. Your work will support safe, interpretable, and sustainable AI deployment for healthcare, environmental monitoring, and autonomous systems. You will have the freedom to shape the project direction, experiment with novel ideas, access state-of-the-art AI and computing facilities, receive tailored training and professional development, collaborate with experts across disciplines, and contribute to open-source tools that advance the wider AI community, and support long-term societal impact.
We welcome applicants from background, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks is a plus but curiosity, creativity, and enthusiasm are equally important. You will join a supportive, interdisciplinary team at Newcastle University and play a key role in building responsible, trustworthy AI for the real-world applications, gaining hands-on experience with the latest AI technologies, contributing to knowledge transfer, and receiving opportunities to develop leadership, and research skills.
Deadline : 18th February 2026
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Synthetic Organic Chemistry: Mechanochemical Synthesis and Reactivity of Next-Generation Organometallic Reagents.
Organolithiums are amongst the most widely used reagents in synthetic chemistry, but are unsustainable given the low natural abundance of lithium (≤20 ppm) which is increasingly required for battery technology. Sodium is >1,000 more naturally abundant than lithium, offering substantial sustainability benefits. This exciting project, in partnership with the globally leading agrochemical company Syngenta, will develop and apply new organosodium reagents in organic synthesis. This will build upon our recent work employing group 1 metals to enable sustainable, mechanochemical processes (see: Nature Synthesis, 2025, ASAP and J. Am. Chem. Soc. 2025, 147, 40895). The aim of the project is to develop a series of new catalytic reactions, enabling the sustainable synthesis of biologically relevant molecules. The student will receive cutting-edge training in synthetic techniques, purification and analysis. Moreover, a 12-week placement and regular meetings with Syngenta will give the student first-hand experience of research in a world-leading industrial setting.
Deadline : 18th January 2026
Connect with Us for Latest Job updates
(11) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in prediction of sediment physical properties through integration of geotechnical and seismic datasets
Project objectives:
· Classify marine sediment types by integrating direct and indirect geotechnical measurements.
· Quantify acoustic and elastic properties of representative sediment classes.
· Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning.
· Assess the reliability of geotechnical correlations across sediment types and quantify associated uncertainties.
The research will combine geotechnical, petrophysical and geophysical approaches. Whole-core properties including P-wave velocity, shear strength and density will be integrated with compositional data to define lithological classes. Effective medium modelling will be used to predict macroscopic elastic properties. These results will be linked to seismic reflection data through impedance-based interpretation workflows, enabling assessment of predictive accuracy across sediment types and data quality levels.
Deadline : 18th January 2026
Polite Follow-Up Email to Professor : When and How You should Write
(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Medicinal Chemistry: High-throughput chemistry and direct-to-biology testing to accelerate drug discovery
The project aims to develop a new approach to drug discovery by developing new methods for synthesising and testing potential drug candidates in high-throughput. One of the barriers to the discovery of new medicines is the time taken to design, synthesise and test compounds through multiple cycles of optimisation. The project will seek to develop an approach to reduce that time through development of high-throughput chemistry approaches that allow the rapid synthesis of analogues with clean-up and direct-to-biology testing to generate biological results. This will involve the development of solution-phase chemistry coupled with solid-phase reaction clean up using tethered reagents that enable pure compounds to be screened without further cumbersome purification. These methods will allow the parallel synthesis and testing of ca. 100 compounds in a single operation, potentially taking less than a week to design, synthesise and test the compounds. Using traditional methods, the equivalent process would take months.
Deadline : 31st January 2026
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Medicinal Chemistry – Hydrophobic warheads to expand covalent drug discovery
The project aims to explore the potential of new warheads for the development of targeted covalent inhibitors for drug discovery. Targeted covalent inhibitors (TCIs) have vast potential to open new therapeutic avenues for undruggable targets but is currently limited by a lack of novel warheads and screening libraries. This project will involve the the design and synthesis of new covalent fragment screening libraries incorporating novel hydrophobic warheads using a Fraglite design approach This covalent fragment set will be designed for screening by both protein NMR and X-ray crystallography: the key fragment screening techniques. It will be screened against potential protein targets via both protein NMR and X-ray crystallography to identify drug discovery start points for high-value cancer targets. An iterative cycle of design-make-test will be used to optimise hit fragments identified through screening.
Deadline : 31st January 2026
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Mechanical: Bioprinted 3D In Vitro Cardiac Models
In vitro models of cardiac tissue are synthetic tissues produced in the lab which allow for the development of organs and the treatment of diseases to be studied. They are produced using cells and biomaterials and are a key part of the drug development pathway for all new drugs. However, current models have some limitations in terms of how well they replicate the responses seen in people. 3D bioprinting techniques are an exciting set of fabrication technologies which build on the principles of 3D printing, but which can process cells and other biological materials. When used in conjunction with other biofabrication techniques they offer a new approach to the development of in vitro models which offers great potential in the development of more effective models which can better evaluate new therapies. This PhD project will focus on the use of bioprinting and biofabrication techniques to create novel in vitro models of cardiac tissue. The project will involve using new biofabrication technologies to create cardiac in vitro models, and a range of biological characterisation techniques to assess their behaviour.
The project builds on previous work which has seen the group develop, patent and spin-out a new bioprinting technology called reactive jet impingement. The group has then integrated this bioprinting technique alongside other technologies to produce in vitro models as part of a European consortium which is studying new treatments for cardiac conditions. The project is interdisciplinary, with an interdisciplinary supervision team led by Professor Kenny Dalgarno, and the successful candidate will be trained in developing and using new processing technologies and in the biological assessment of tissue engineered in vitro models, with the training tailored to the background of the successful applicant.
Deadline : 18th February 2026
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Mechanical Engineering: Particle Transport in Porous Media in Subsurface Carbon Storage Applications
Carbon capture and storage (CCS) strategies aim to mitigate climate change in the support of the UK’s net-zero target for 2050. However, injection of CO2 into deep saline aquifers initiate a series of geochemical reactions leading to mineral dissolution followed by the precipitation of secondary minerals. From a fluid dynamics perspective, the newly formed solids can be regarded as particles suspended within the pore-scale flow. The primary objective of this project is to investigate the transport, migration, and accumulation of precipitated particles in CO2–water–rock systems using computational fluid dynamics (CFD) coupled with discrete element method (DEM).
The research outcomes will provide critical insights into the microscale transport phenomena relevant to subsurface storage performance, including permeability evolution and CO2 containment. Furthermore, the framework developed here can be extended to related fields such as contaminant transport, geothermal systems, and mineral recovery.
Deadline : 18th February 2026
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Mechanical Engineering: Engineering a Synovium-on-a-Chip Platform for Human-Relevant Inflammation Studies
This PhD will develop a Synovium-on-a-Chip, using 3D bioprinting, microfluidic engineering, and computational fluid dynamics (CFD), to create a dynamic, perfused system that mimics the human synovial environment. The platform will allow us to test how gut-derived immune signals influence joint inflammation, providing an advanced tool for disease modelling and drug discovery.
Deadline : 18th February 2026
(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Marine Ecology – Ecosystem Dynamics of Mesophotic Coral Reefs
The role complements a broader NERC funded project investigating Coral Reef Dynamics across Longitude, Latitude, and Depth. The goal is to further our ecological understanding of coral reefs across their full spatial extent to provide a groundbreaking framework with which to assess the shape and robustness of current and future assembly of coral reef biodiversity.
You will design and carry out your own research, with the support of an international supervisory team. Depending on your current and desired skills and interests, your PhD will combine fieldwork, lab-work, and/or data analysis, to address topics related to one of: Understanding depth-related plasticity in the physiology and behaviour of mesophotic reef fish.
Identifying depth-related changes in the structure and robustness of the ecological networks supporting reef fish communities at different positions along depth, latitude, and longitude gradients; challenging these networks under hypothesized future assemblage changes.
Determining how coral reef fish food webs and energy pathways are connected along extended depth gradients of 0-90 meters.
Based in Newcastle, and with international supervision, you will receive training and skills in some of the following: meta-barcoding, stable isotope analysis, trophic-web analysis, Bayesian statistics, wet-lab experimentation – respirometry, fieldwork. Previous experience in any of these areas is useful but not essential. Diving fieldwork is available with suitable qualifications and experience.
Deadline : 2nd February 2026
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Machine Learning-Based MIMO Radar Sensing for All-Weather Perception in Autonomous Vehicles
Autonomous vehicles are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project covers the aspects of sensing, detection and classification in radar-based perception.
Deadline : 18th February 2026
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Just Transformations to Low Carbon Living
This PhD will use participatory research methods to co-produce policy-relevant research on just transitions to low carbon living in North East England. The successful candidate will be part of an interdisciplinary team based at Newcastle University, and will play a key role in designing and delivering research that supports just transition initiatives in the region.
This PhD is affiliated to the JUST (Joined-Up Sustainability Transformations) Centre: a new ESRC-funded multi-university consortium bringing together five universities in the North of England with partners in the policy, innovation, business, local government, community, and voluntary sectors. JUST aims to generate innovative, place-based strategies that move communities towards fair and democratic low carbon futures.
The successful candidate will join the North East England Place-Based Research Team (led by Prof. Danny MacKinnon) and the “Principles of Justice” Thematic Working and Interest Group (led by Prof. Derek Bell). You will work closely with a wide range of local stakeholders to co-design and co-deliver Participatory Action Research (PAR) case studies that explore how and when principles of justice can be successfully embedded in place-based initiatives that promote the transition to low carbon living. You will collaboratively explore which principles of justice are most important for a just transition in North East England and how to co-design tools or frameworks that support local stakeholders to join up social and economic justice with environmental sustainability.
Deadline : 9 March 2026
(20) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in High-Fidelity Simulations of Geological CO2 Sequestration (SIGECOS)
We are seeking a highly motivated PhD candidate with interests and skills in computational modelling and simulations, fluid dynamics, mechanical engineering, physics and applied mathematics. You should have experience in one or more of the following: numerical methods, high-performance computing (HPC), Computational Fluid Dynamics (CFD), applied mathematics, physics, engineering or subsurface flow modelling. Enthusiasm, willingness to learn, and the ability to think creatively about complex physical systems are just as important as specific technical expertise.
This PhD project—High-Fidelity Simulations of Geological CO2 Sequestration (SIGECOS)—aims to advance our understanding of how supercritical CO2 behaves when injected into deep saline aquifers. Using cutting-edge numerical methods and high-resolution simulations, you will explore key physical processes governing CO2 plume migration, trapping mechanisms, and fluid–rock interaction under realistic subsurface conditions. The goal is to generate insights that improve the safety, efficiency, and predictability of geological CO2 sequestration and storage.
You will have the opportunity to co-shape the direction of the project, tailoring the modelling approaches, physical focus areas, or computational strategies to your interests—whether that involves large-scale reservoir simulation, pore-scale physics or supercritical CO2 behaviour. The project will be developed within a vibrant research environment, and may link to a broader programme on high-fidelity modelling for net-zero technologies.
Deadline : 18th February 2026
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Computational Chemistry – Training force fields for computer-aided drug design with machine learning.
The state-of-the-art in computer-aided drug design is physics-based modelling, in which candidate drugs and their targets are simulated at the atomistic level. The most widely-used tool for this are molecular mechanics force fields, such as those developed by the Open Force Field Initiative [https://doi.org/10.1021/acs.jpcb.4c01558], but they lack accuracy for predictive modelling. Transferable machine learning potentials, like MACE-OFF [https://doi.org/10.1021/jacs.4c07099], effectively achieve quantum mechanical accuracy for small organic molecule energetics, but are too slow for routine use in medicinal chemistry.
This collaborative, industry-funded, computational project will i) use state-of-the-art machine learning potentials to rapidly generate new condensed phase training data, ii) develop automated workflows to train molecular mechanics force fields against these accurate data sources, and iii) validate force field accuracy with industry partners for computer-aided drug design applications.
The successful applicant will work closely with project partners at SandboxAQ. The supervisory team will provide highly sought-after training in the fields of computational molecular modeling, medicinal chemistry, and machine learning. As such, this project is ideal for a candidate with ambitions towards a career in the pharmaceutical industry or academic computational chemistry.
Deadline : 18th January 2026
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Chemical Engineering: Advancing Fermented-Sugar Pathways for Sustainable Aviation Fuel Production
The project aims to identify high-performing microbial species capable of efficiently converting mixed C5/C6 sugars into higher alcohols with excellent yield and productivity. Robust yeast and bacterial strains will be studied alongside continuous, integrated fermentation–separation processes to enhance efficiency and reduce fuel costs and lifecycle greenhouse gas (GHG) emissions.
Deadline : 18th February 2026
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Chemical Engineering
Engineered biochar – a durable solid form of carbon originating from the partial combustion of organic matter that can be added to soils – is rapidly gaining attention as a scalable carbon dioxide removal (CDR) and sequestration solution. But what makes biochar and other pyrogenic carbon (PyC) (like charcoal), last for decades, millennia, and even hundreds of millions of years? To answer this, we will look to nature’s experiment with fire! Wildfire-derived charcoal, a recalcitrant form of PyC, has long shaped landscapes and stabilised carbon in soils, and is the form in which the first evidence for the dawn of terrestrial plants over 420 million years ago was found. The chemical and structural drivers of PyC’s long-term stability are not yet fully understood. Unravelling those features is key to designing engineered carbon materials capable of removing and storing carbon on the geological timescales required to address climate change.
To bridge this gap, this project will characterise wildfire charcoal from historic fires with known ages (years to decades to 174 MA old) to examine compositional evolution and preservation over geological time. By comparing these with freshly engineered biochars, we can determine whether persistence arises from the biomass type, formation process and/or the final composition and structure itself. We will quantify these features and engineer biochar with enhanced long-term carbon stability using techniques including Raman spectroscopy, X-ray diffraction (XRD), solid-state ¹³C NMR, leaching and accelerated ageing tests.
Deadline : 18th February 2026
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Chemical Engineering – Electrochemical biosensors for point-of-care monitoring of life-threatening cell breakdown in blood cancers.
The rapid breakdown of malignant haematologic cells (i.e., blood cancers) either spontaneously or following therapy, known as tumour lysis syndrome (TLS), is a life-threatening oncologic emergency. For high-risk patients, the levels of critical biomarkers (e.g., uric acid, potassium, and phosphate) must be monitored every 4-6 hours. This is currently achieved through frequent blood draws and laboratory analyses that are not only invasive and resource-intensive but also lack the temporal resolution required for prompt clinical intervention, leading to preventable deaths in TLS patients. While wearable biosensors show great promise for real-time and non-invasive monitoring of diverse biomarkers, there is currently no biosensor that can reliably detect key TLS biomarkers.
This PhD project will focus on developing novel biosensors that integrate platform sensing technology with tailored electroactive materials to enable precise and reliable detection of key TLS-related biomarkers using robust, user-friendly electrochemical methods. Early detection and timely intervention of TLS will prevent organ dysfunction and mortality, improving patient outcomes and quality of life. Given the high healthcare costs associated with TLS management (e.g., hospitalisation, medications, laboratory testing, and monitoring), point-of-care monitoring has the potential to significantly reduce inpatient time, alleviate pressure on the NHS, and lead to substantial healthcare savings.
This studentship is ideal for candidates passionate about applying engineering innovation to address unmet clinical needs. During your PhD, you will gain the practical skills needed to drive innovation in designing the next generation of biosensors using advanced materials. You will be supported by a multidisciplinary supervisory team with extensive expertise in novel materials design, data science, and the clinical management of TLS. You will develop expertise in electrochemical biosensor design and development, progressing the technology toward clinical readiness. You will help strengthen the UK’s leadership in point-of-care diagnostics for cancer-related emergencies while building valuable expertise at the health–engineering interface.
Deadline : 18th February 2026
(25) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Biofouling Impact on Dynamic Cables for Offshore Floating Wind
Offshore Floating Wind (OFW) is key to unlocking deep-water renewable energy and achieving the global Net Zero targets. However, dynamic power cables that connect floating wind turbines to the seabed remain one of the challenging issues in the engineering analysis and design of floating wind applications. Over time, these subsea cables become coated with soft and hard biofouling – marine organisms that increase drag, weight and thermal resistance – potentially modifying the coupled electro-mechanical-fluid loading and causing fatigue and early failure.
This PhD project will investigate how biofouling affects the hydrodynamic, thermal and fluid-structure interaction performance of dynamic flexible cables and develop novel engineering solutions to enhance their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/) and numerical methodology to quantify biofouling impacts on flow-induced vibration phenomena, structural responses and operational performance of dynamic cables, and to evaluate sustainable antifouling materials, structural design, optimisation and maintenance strategies.
The successful candidate will join a multidisciplinary team working at the frontier of offshore and subsea engineering and renewable energy research supported by industry partners. They will develop advanced skills in experimental hydrodynamics, materials characterisation and computational simulation – highly sought after in the UK’s growing offshore energy sector.
Deadline : 18th February 2026
(26) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Bioengineering – Biomechanical risk factors for bone fracture
We are looking for an enthusiastic engineer to help us explore the mechanics of bone in patients with brittle bone disease, who is familiar with finite element modelling techniques and scripting.
Osteogenesis imperfect (OI), also known as ‘brittle bone disease’ is a genetic condition which affects the development of type I collagen. Patients with OI have poor mineralisation of their bones and consequently are much more likely to suffer bone fractures. Fractures are most common in patients when they are children and also later on in life (between 60 and 80). There is huge variability in how well different patients respond to different treatments and we cannot currently predict for an individual how severe their disease will be or the best treatment pathway.
This project is in collaboration with Dr Richie Abel from Imperial College London, who is an expert in bone biology and will provide the high-resolution computed tomography (CT) scans of the bone. The overall goal of the project is to use computational approaches to map both the modulus and the Poisson’s ratio of the bone in patients with and without OI to improve our understanding of the mechanical consequence of the disease. Model results will be validated with experimental test data. This project will harness new software capabilities to better understand bone mechanics, providing insight into the cause of OI fractures and its management.
The successful candidate will have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing on biological tissues and medical image processing. The studentship includes many opportunities for the candidate to build their professional network by presenting their work at conferences and discussing research findings with clinicians and academics.
Deadline : 18th February 2026
(27) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Bio-electronics – Localising invisible breast cancers during surgery
We are looking for a highly motivated candidate with a background in electronic engineering, physics or a related discipline. Strong practical skills, an interest in biomedical research, and the ability to work independently are essential. Prior experience/knowledge in Electromagnetism, COMSOL, microfabrication, and PCB design are desirable but not essential.
Breast cancer is the most common malignancy in the UK, with over 55 000 new diagnoses annually. Surgery (lumpectomy or mastectomy) is the best line of treatment. To enable surgeons to identify the cancer tissue, radiologists insert a localisation device (RFID, magnetic seed) into the tumour pre-operatively. Wireless methods hold promise however, due to the scale of current RFID tags, delivery is problematic for both clinicians and patients.
The PhD provides an opportunity to develop novel micro-electronic tags for accurate excision of breast cancer. The research will involve device design and fabrication within engineering cleanrooms, in vitro testing and collaboration with consultant radiologists and surgeons from Gateshead Breast unit to assess device performance and clinical safety.
Deadline : 18th February 2026
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in Astrophysics – Weighing Galactic black holes with X-rays
Material falling onto a black hole glows brightly in X-rays, lighting up the vicinity of the event horizon. This process happens for black holes in our Galaxy that are in a close binary system with a normal star. Measuring the mass of these black holes informs on their formation mechanism, but traditional optical techniques are not accessible for ~2/3 of the known systems due to obscuration. This PhD project will focus on making pioneering mass measurements of black holes using the X-ray signal, for which obscuration is not a problem. The technique we will use is X-ray reverberation mapping – exploiting the echo that is created when X-rays from close to the black hole reflect off the accreting material on their way to our telescope. There will be scope for both observational and theoretical work, as we develop ever more sophisticated reverberation mapping models that account for general relativistic and radiative transfer effects, and apply them to state-of-the-art data from observatories such as the NASA missions NICER, NuSTAR and IXPE.
Deadline : 31 January 2026
(29) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship – Function on Demand, Degrade on Disposal: Next-Generation Polymers for Sustainable Cleaning
Laundry contributes significantly to energy and water use. UK households spend over £2.16 billion per year on electricity and water to run washing machines. Improving the sustainability of these everyday processes is essential for meeting net-zero targets and reducing environmental impact. High-performance laundry products play a vital role by enabling cleaning at lower temperatures and with less water. A key component in these products are polymer additives, which enhance cleaning performance by aiding in soil removal and preventing soil from redepositing back upon fibres. These polymers are not biorenewable and often are not readily biodegradable and thus have potential to persist in the environment and biodegradable and sustainable alternatives are urgently needed. This project will develop a new class of biodegradable, polysaccharide additives for use in laundry formulations, with a focus on performance, scalability, and environmental degradation. The project will appeal to those interested in applying chemistry to real world problems, and will benefit from close collaboration with scientists at Procter & Gamble’s Newcastle Innovation Centre.
Deadline : 18th January 2026
(30) PhD Degree – Fully Funded
PhD position summary/title: NUAcT PhD Studentship: Law and the Nonhuman
Newcastle Law School at Newcastle University invites applicants for a doctoral studentship in law and the nonhuman. This is an open call and candidates should apply with their own project proposal based on their own interests. The theme of law and the nonhuman can encompass a wide array of projects, including projects, for example, focusing on the rights of nature, on issues relating to ocean law, on nonhuman animal law, on environmental law, or on more theoretical approaches relevant to the theme of law and the nonhuman (see below for more examples). Projects proposals that take a critical theory lens and which seek to centre relationships between the human and the nonhuman are particularly welcome, including those that draw on, for example, feminist, queer, postcolonial/TWAIL/decolonial, posthuman, Marxist, and other critical legal approaches. Interdisciplinary or transdisciplinary projects are strongly encouraged. In addition, projects that focus on global or transnational issues, either wholly or in part, are welcomed.
The successful candidate will be supervised by Dr Emily Jones alongside a second supervisor who will be chosen based on the best fit with the project. There is a possibility to have a supervisor from another discipline, depending on the needs of the project. The selected candidate will join a vibrant research community in the School and Newcastle University, which includes the Nonhuman Law Research Group. Candidates are encouraged to apply with a project that they are interested in which can draw on a variety of methods as appropriate to the project design. Project ideas include, but are not limited to:
- Theoretical projects that think through nonhuman legal issues in relation to, for example, feminist, queer posthuman, Marxist, TWAIL/postcolonial/decolonial or other relevant theories
- Research proposals that focus on law and art/creative processes, including creative writing and music, and the nonhuman
- Research that centres Indigenous knowledge and nonhuman legal issues
- Discussions of human-nonhuman relationality in the law
- Projects focusing on the theory and application of the rights of nature
- Research into issues surrounding the nonhuman and ocean or water law
- Investigations of nonhuman elements and their regulation e.g. pollution, plastics etc.
- Analyses of nonhuman animal law, particularly situating nonhuman animal issues in the wider context of nonhuman justice
- Projects that bring law and the social sciences/anthropology together which seek to understand nonhuman legal issues in relation to a specific place or context
- Analyses of nonhuman legal issues in conversation with other disciplines including the arts and humanities, the social sciences and the wider sciences (e.g. marine science or environmental science)
- Discussions of geoengineering and other “climate-fix” technologies
- Focused analyses of key environmental law principles from a nonhuman perspective
Deadline : 20 February 2026
(31) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship: Towards Resilient Water Supply Infrastructure and Services in Mexico City
Mexico is experiencing an escalating water security crisis shaped by environmental pressures, rapid urbanisation, and complex governance challenges. Nowhere is this more evident than in Mexico City, where chronic water scarcity, climate variability, and weakened infrastructure converge. Major reservoirs and aquifers that supply the capital such as Cutzamala and Lerma are under severe strain, and more than 100 of Mexico’s aquifers are overdrawn. Nearly half of residents lack reliable access to safe water, while extensive leakage across aging systems further reduces supply. These problems are intensified by governance gaps, fragmented administrative boundaries, and historical mismanagement of drainage and supply systems across the Mexico City Metropolitan Area (MCMA).
This project will examine the drivers and consequences of water insecurity in Mexico City, with the goal of identifying sustainable, equitable, and long-term strategies for resilient water resource management. The research will explore three core dimensions: transboundary water dynamics, institutional and policy effectiveness, and the impacts of climate variability on urban water systems. Key questions will address how upstream management influences city-level water access, how governance structures shape policy outcomes, and how future climate conditions will affect resilience.
Mixed-methods approach will be adopted, including hydrological and infrastructure assessments, analysis of transboundary agreements, and a political economy review of decision-making. Governance evaluation will combine policy analysis with interviews across government, utilities, and civil society. Modelling and scenario planning will project future supply conditions and assess nature-based and multi-benefit infrastructure solutions to support long-term water security.
Deadline : 30 January 2026
(32) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship: Rooted in Resilience: Optimising the Plant-Soil System for Flood-Resilient Rain Gardens
Climate change is driving more intense storms, putting urban drainage systems under pressure. Rain gardens (vegetated basins that manage stormwater) are a key sustainable solution, but their long-term performance often suffers due to generic design approaches that overlook plant ecology. This PhD project will transform rain garden design by linking plant traits to hydrological and ecological outcomes, ensuring resilience under alternating drought and flood stress.
Working with the Royal Horticultural Society and Robert Bray Associates, you will combine field studies of mature rain gardens with controlled experiments to assess how traits such as canopy interception, transpiration, and rooting depth influence stormwater retention, soil evolution, and biodiversity. Using these insights, you will develop a classification system and decision-support framework to guide practitioners in selecting plants and designing rain gardens tailored to site conditions and climate adaptation goals.
This research offers real-world impact, reducing flood risk, enhancing urban green infrastructure, and shaping future design standards. Ideal for candidates passionate about sustainability, plant science, and nature-based engineering innovation.
Deadline : 30 January 2026
(33) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship: Real-Time River Water Quality Forecasting through Integrated Hydrodynamic and Surrogate Modelling
This PhD project aims to develop a computationally efficient framework for the real-time prediction of river water quality following contamination events associated with Combined Sewer Overflows (CSOs). Such events present increasing risks to public health, ecosystems and urban water environments, particularly under pressures from climate change, urbanisation and ageing infrastructure. Although high-fidelity numerical models can simulate hydrodynamic and pollutant transport processes, their computational cost limits their suitability for real-time emergency decision-making. This project addresses this challenge by combining physics-based modelling with data driven surrogate approaches.
The first stage of the project will involve the development of a multi-layer hydrodynamic model capable of representing key three-dimensional flow processes in riverine and estuarine systems. This model will be coupled with advection–diffusion–reaction equations to simulate pollutant transport, mixing and biochemical processes.
To enable rapid prediction, a machine-learning surrogate model based on Gaussian process regression will be developed and trained using datasets generated by the high-fidelity numerical solver. The surrogate will emulate key hydrodynamic and water quality responses while providing robust uncertainty quantification to support reliable decision-making. Evolutionary algorithms will be employed to efficiently explore the parameter space and undertake sensitivity analyses.
The integrated framework will be validated using analytical test cases, laboratory experiments, and field measurements. It will then be applied to a real-world case study on the Ouseburn in Newcastle upon Tyne to demonstrate its capability for real time water quality forecasting and its ability to support decision-making aimed at protecting river users from health risks.
Deadline : 30 January 2026
(34) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship in prediction of sediment physical properties through integration of geotechnical and seismic datasets
Offshore wind energy is expanding rapidly, but optimising site surveys for project planning remains challenging. Geotechnical site investigations (SI) may cost up to £500,000 per borehole, introducing significant financial and scheduling risks. Suboptimal data collection can increase costs, require additional surveys, and delay investment decisions. Reducing SI impacts is especially important for Floating Offshore Wind (FOW), where characterising 300+ anchor locations may be required to support early project engineering.
Predicting key physical and mechanical properties of marine sediments—such as shear strength, stiffness, and density—is central to designing offshore infrastructure, influencing foundations, anchors, cable burial, and overall construction risk. Although SI combine geophysical and geotechnical data, quantitative relationships between cone penetration tests, borehole measurements and seismic reflection data remain limited due to a lack of systematic comparisons and underused legacy datasets.
This project will develop a framework to predict sediment properties directly from geophysical data. Legacy SI data offer a valuable resource for building training datasets linking measured properties to geophysical parameters. Using these datasets, the project will improve the reliability of geotechnical parameters inferred from seismic data.
A robust methodology for predicting sediment properties from geophysical data could reduce the number of boreholes required before investment decisions, enabling faster and more cost-effective offshore wind development.
Deadline : 18th January 2026
About Newcastle University, England –Official Website
Newcastle University (legally the University of Newcastle upon Tyne) is a public research university based in Newcastle upon Tyne, North East England. It has overseas campuses in Singapore and Malaysia. The university is a red brick university and a member of the Russell Group, an association of research-intensive UK universities.
The university finds its roots in the School of Medicine and Surgery (later the College of Medicine), established in 1834, and the College of Physical Science (later renamed Armstrong College), founded in 1871. These two colleges came to form the larger division of the federal University of Durham, with the Durham Colleges forming the other. The Newcastle colleges merged to form King’s College in 1937. In 1963, following an Act of Parliament, King’s College became the University of Newcastle upon Tyne.
The university subdivides into three faculties: the Faculty of Humanities and Social Sciences; the Faculty of Medical Sciences; and the Faculty of Science, Agriculture and Engineering. The university offers around 175 full-time undergraduate degree programmes in a wide range of subject areas spanning arts, sciences, engineering and medicine, together with approximately 340 postgraduate taught and research programmes across a range of disciplines.The annual income of the institution for 2021–22 was £543.2 million of which £109.6 million was from research grants and contracts, with an expenditure of £624.3 million.
Disclaimer: We try to ensure that the information we post on VacancyEdu.com is accurate. However, despite our best efforts, some of the content may contain errors. You can trust us, but please conduct your own checks too.
Related Posts
