University of Cambridge, United Kingdom 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 University of Cambridge, United Kingdom.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: MRC BSU PhD Studentship
The Medical Research Council (MRC) Biostatistics Unit (BSU) is one of the largest groups of biostatisticians in Europe, and a major centre for research, training and knowledge transfer in biostatistics. We develop, apply and promote innovative statistical and data science approaches to advance biomedical science and human health. The BSU current research portfolio is organised into five main themes that span the scientific research spectrum from basic science to population health and respond to current scientific needs in biomedicine.
We welcome applications from students who wish to apply innovative statistical methods to real biomedical problems in order to deliver key insights into human health and disease. One highly competitive fully funded (covering University fees and stipend) three-year studentship will be available to a UK applicant from January 2027. Our departmental funding includes a generous travel and training budget.
The Unit is actively seeking to increase diversity among its doctoral students, including promoting an equitable representation of men and women. The Unit therefore especially encourages applications from under-represented groups, including women and minority ethnic groups.
Deadline : 21 September 2026
(02) PhD Degree – Fully Funded
PhD position summary/title: GlaxoSmithKline-funded PhD studentship: Immune Ageing (Fixed Term)
The UK population is getting older, with nearly 1 in 5 individuals over the age of 60 and over half a million aged 90 or older (2021 Census). This is important, because ageing is strongly associated with altered immune function, leading to increased susceptibility to infectious and inflammatory diseases, which are major contributors to morbidity and mortality in older adults. A major limitation to our understanding of human immune age has been a reliance on analysis of few immune traits in comparatively small cohorts with limited representation of the oldest individuals. To overcome this, we have integrated multiple datasets to identify and validate latent age-related trajectories, capturing quantitative traits reflecting immune exposure and response, and uncovering highly stereotyped and non-linear trajectories of immune ageing. Here, we propose to build on our existing work to quantify multiple immune age metrics in a longitudinal population of ageing individuals undergoing annual immune challenge in the form of vaccination. We will relate these immune age metrics to a variety of outcomes including correlates of vaccine protection and clinical outcomes with the aim of inferring mechanistic processes that drive immune ageing. Students will use multi-omic single cell methods to identify cell subpopulations associated with both chronological and immunological ageing (defined by a range of different ageing metrics), their associated differentiation trajectories and multi-omic characteristics and will relate these to the magnitude, breadth and efficacy of vaccine-induced protection. These data will deeply characterise the aged immune response, explore the mechanism of changes occurring and support development of experimental medicine interventions to modulate aged immunity.
The successful candidates will each undertake a four-year research project with the overall aims of (1) characterising aged immune responses, (2) exploring how they change longitudinally in an ageing population, and (3) investigating how this knowledge can be exploited to better modulate aged immunity. Depending on the specific interests of the student, individual projects may include exploitation of computational machine learning approaches in concert with wet-lab experiments on aged samples. Wet-lab experiments will include generation of multi-omic single cell datasets alongside immune organoid models, while dry-lab work will seek to interpret age-related changes and their impact on immunity using advances in the capabilities of machine learning/AI techniques.
Deadline : 4 September 2026
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Studentship in Monitoring and Increasing LLM Safety
The first 1.5 years of this PhD are scoped out and will be about investigating and carrying out either project 1 or project 2 (described below). After these projects have been completed to the highest standard, you will together with your supervisor and Coefficient Giving decide how to proceed, and what to investigate next.
Project 1: Test for straightforward meaning of CoT and mitigate deceptive behaviour via “perturbation methods”.
First apply a CoT perturbation method (e.g. applying paraphrasing to intermediate outputs). You then compare the final outputs after the CoT is perturbed with baseline final outputs. Performance deterioration after applying perturbation methods, indicates the model was using words in the CoT in a non-straightforward way. If you find performance deterioration after applying perturbation methods, the next step is investigating (for example using mechanistic interpretability) the underlying cause e.g. the model using a secret code or prompt hacking itself.
Project 2: Train for transparency using a human predictor
Use a human (or AI imitating human behavior, e.g. an LLM) to evaluate whether the final model outputs (and counterfactual outputs) can be predicted based on the CoT. The accuracy of this human predictor is a measure of reasoning transparency and can be used as reward during training.
Deadline : 30 July 2026
(04) PhD Degree – Fully Funded
PhD position summary/title: Marie Sklodowska-Curie Early Stage Researchers- Bayesian inference of pulsatile flow through compliant boundaries
Flow-MRI (magnetic resonance imaging) is a non-invasive imaging method that visualizes fluid flows in the body in 4D (3 spatial and 1 time dimension) without using ionizing radiation. It holds great promise for comprehensive characterization of blood velocity, particularly in the heart and major blood vessels, but is currently hindered by low signal-to-noise ratio (SNR) and low spatial resolution.
The Principal Investigator’s research group has developed a method that assimilates sparse and noisy Flow-MRI data directly into a computational fluid dynamics (CFD) simulation. This method uses Bayesian inference, which is also known as probabilistic machine learning. The Bayesian inference code wraps around a differentiable Finite Element Method code, which combines adjoint methods with Laplace’s method to assimilate data and estimate uncertainties.
The objectives of the proposed study are to (i) extend Bayesian inference of Flow-MRI data to 4D pulsatile flows within compliant boundaries; (ii) implement, test, and validate the results with data from compliant test objects in MRI scanners; (iii) increase the image resolution and the predictive accuracy of derived information such as pressure gradients and wall shear stress, and (iv) assess the clinical relevance of this information by working with clinicians.
Deadline : 22 July 2026
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD (Fixed Term)
The Project: This 3 year PhD project is embedded in the NIHR Health Protection Research Unit in Vaccines & Immunisation, a collaboration between the UK Health Security Agency (UKHSA), the London School of Hygiene & Tropical Medicine (LSHTM), University College London (UCL) and the University of Cambridge.
Based at the University of Cambridge and supervised by Professor Caroline Trotter, the student who should have or should expect to obtain a minimum of a UK 2:1 Honours Degree (or equivalent) in a relevant subject, will work closely with colleagues at UKHSA and other members of the HPRU.
The student will develop a framework for making decisions about vaccines that more formally considers the effect on the immunisation programme as a whole. They will then apply this draft framework to specific case studies and assess whether and how decision-making could be influenced, leading to further refinement.
The student will develop skills in infectious disease epidemiology, mathematical modelling of vaccine preventable diseases and health economics. The public are ultimately the ‘vaccine consumers’ and as such should be involved in framing and shaping vaccine research, so the student should also develop and execute a plan for public involvement and engagement.
Deadline : 10 July 2026
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD studentship: Single-cell spatial multi-omics for cancer biology
In the Wang Group, we develop and apply interdisciplinary technologies that bridge high-resolution spatial biology and genome-wide discovery. By integrating multi-omic sequencing and quantitative imaging, we work towards a multi-scale understanding of how molecular composition and subcellular organisation shape cell function, plasticity and disease. A central biology focus of the lab is extrachromosomal DNA (ecDNA) circular DNA elements that drive oncogene amplification, intratumour heterogeneity and therapeutic resistance across many aggressive solid cancers.
This PhD project will help develop and apply cutting-edge single-cell and spatial multi-omic approaches that link molecular signatures to cancer cell vulnerabilities. Working at the interface of molecular, chemical and optical method development and cancer biology, the student will build tools that connect molecular mechanisms of gene regulation to cellular phenotypes in cancer cells, and use them to dissect how ecDNA is organised, regulated and exploited in cancer.
Deadline : 6 July 2026
(07) PhD Degree – Fully Funded
PhD position summary/title: ERC PhD studentship in Seeking precursors of Pyrophoricity
Materials response to harsh irradiation, temperature and corrosive media is preventing the successful exploitation of innovative nuclear fusion, advanced fission technologies for sustainable energy production and human exploration of faraway planets. Specifically, materials degradation and early failures hinder these scientific longstanding endeavours. The current paradigm to tackle these issues is to implement mitigating solutions or to characterise the surrounding environment to understand failure initiation and propagation. URÅNIA shifts this approach by focusing directly on understanding the incubation stage prior to initiation events. The Principal Investigator’s research group will demonstrate the URÅNIA methodology by: i) creating a novel gold standard to reveal the incubation stage of materials degradation phenomena; ii) revealing precursors affecting the transition from incubation to initiation, iii) linking precursors nanoscale effect to macroscopic degradation behaviour.
The aim of this post is to: (i) initiate sample preparation and undergo training to work in active laboratories for production and characterisation of 3D printed UC. (ii) analyse and perform High Temperature Environmental Scanning Electron Microscopy (HT-ESEM) initiation and incubation experiments.
Deadline : 5 July 2026
(08) PhD Degree – Fully Funded
PhD position summary/title: ERC PhD studentship in Seeking precursors of Stress Corrosion Cracking
Materials response to harsh irradiation, temperature and corrosive media is preventing the successful exploitation of innovative nuclear fusion, advanced fission technologies for sustainable energy production and human exploration of faraway planets. Specifically, materials degradation and early failures hinder these scientific longstanding endeavours. The current paradigm to tackle these issues is to implement mitigating solutions or to characterise the surrounding environment to understand failure initiation and propagation. URÅNIA shifts this approach by focusing directly on understanding the incubation stage prior to initiation events. The Principal Investigator’s research group will demonstrate the URÅNIA methodology by: i) creating a novel gold standard to reveal the incubation stage of materials degradation phenomena; ii) revealing precursors affecting the transition from incubation to initiation, iii) linking precursors nanoscale effect to macroscopic degradation behaviour.
The aim of this post is to: (i) support the development of SCC initiation tool, perform SCC initiation and incubation testing, (ii) use of advanced microscopy techniques to reveal precursors of SCC
Deadline : 5 July 2026
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(09) PhD Degree – Fully Funded
PhD position summary/title: Junior Clinical Training Scholarship (Internship) in Small Animal Studies
Applications are invited for this one-year post-graduate training programme based in the Queen’s Veterinary School Small Animal Hospital. On site accommodation is available for £300 per month including bills.
Junior Clinical Training Scholars will receive training and tuition as they rotate through anaesthesia, cardiology, diagnostic imaging, orthopaedics, dermatology, internal medicine, neurology, oncology, clinical pathology and soft tissue surgery and be supervised by recognised specialists in each field. Scholars will also have responsibility for primary care cases, and be involved in supervision and guidance of final year veterinary students. Scholars will be an integral part of the out of hours care of animals within the hospital, especially within the intensive care unit.
Deadline : 30 June 2026
About The University of Cambridge, United Kingdom – Official Website
The University of Cambridge is a collegiate research university in Cambridge, United Kingdom. Founded in 1209 and granted a royal charter by Henry III in 1231, Cambridge is the second-oldest university in the English-speaking world and the world’s fourth-oldest surviving university. The university grew out of an association of scholars who left the University of Oxford after a dispute with the townspeople. The two English ancient universities share many common features and are often jointly referred to as Oxbridge.
Cambridge is formed from a variety of institutions which include 31 semi-autonomous constituent colleges and over 150 academic departments, faculties and other institutions organised into six schools. All the colleges are self-governing institutions within the university, each controlling its own membership and with its own internal structure and activities. All students are members of a college. Cambridge does not have a main campus, and its colleges and central facilities are scattered throughout the city. Undergraduate teaching at Cambridge is organised around weekly small-group supervisions in the colleges – a feature unique to the Oxbridge system. These are complemented by classes, lectures, seminars, laboratory work and occasionally further supervisions provided by the central university faculties and departments. Postgraduate teaching is provided predominantly centrally.
Cambridge University Press, a department of the university, is the oldest university press in the world and currently the second largest university press in the world. Cambridge Assessment, also a department of the university, is one of the world’s leading examining bodies and provides assessment to over eight million learners globally every year. The university also operates eight cultural and scientific museums, including the Fitzwilliam Museum, as well as a botanic garden. Cambridge’s libraries, of which there are 116, hold a total of around 16 million books, around nine million of which are in Cambridge University Library, a legal deposit library. The university is home to, but independent of, the Cambridge Union – the world’s oldest debating society. The university is closely linked to the development of the high-tech business cluster known as ‘Silicon Fen’. It is the central member of Cambridge University Health Partners, an academic health science centre based around the Cambridge Biomedical Campus.
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