Fixed-term

Why do some people escape genetic risk? Multi-biobank study of immune-mediated inflammatory diseases

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Details Most people at high genetic risk of immune-mediated inflammatory disease never develop disease, while some develop disease despite apparently low inherited risk. These “genetically discordant” individuals may reveal mechanisms of disease protection, resilience and susceptibility that are missed by conventional genetic risk prediction. This PhD will use UK Biobank, with replication in All of Us, to study why genetic risk does or does not translate into clinical disease. The project will integrate polygenic risk, electronic health records, environmental exposures and sequencing data across rheumatoid arthritis, axial spondyloarthritis and psoriatic disease. Study 1: Environmental modifiers of genetic risk The student will identify individuals with high (common variant) polygenic risk who remain disease-free, and individuals with low genetic risk who develop disease. They will test whether lifestyle and other potentially modifiable factors help explain resilience or susceptibility. Study 2: Rare variant discovery The student will use sequencing data to identify rare coding variants, protective alleles and genetic modifiers associated with discordant disease status. This study will investigate whether genetic architecture beyond common polygenic risk helps explain why some individuals unexpectedly develop disease, while others remain protected. Study 3: Pre-diagnostic health trajectories The student will examine whether longitudinal health records before diagnosis reveal distinct trajectories into disease. This will include temporal patterns of comorbidity accumulation before clinical onset. The supervisory team brings together clinical epidemiology, rheumatology, and internationally recognised leadership in immune-mediated disease genetics, providing an exceptional environment for training at the interface of genetic and traditional epidemiology. The student will gain training in genetic epidemiology, longitudinal modelling, rare variant analysis, and biobank-scale health data science, preparing them for a career in academia, biotechnology, pharmaceutical research, precision medicine or applied health data science. Eligibility   Candidates should hold, or be close to obtaining, a first-class or strong upper second-class honours degree, or equivalent, in a relevant quantitative, biomedical or population health discipline. Suitable backgrounds include epidemiology, biostatistics, bioinformatics, statistical genetics, data science, computational biology, public health, genetics, medicine or a related field. We particularly encourage applications from candidates with strong quantitative aptitude, experience using statistical software such as R or Python, and an interest in applying large-scale health and genomic data to clinically important questions in immune-mediated disease. Prior experience with epidemiological analysis, regression modelling, electronic health record data, polygenic risk scores, sequencing data or longitudinal analysis would be advantageous. Candidates should be intellectually curious, methodologically rigorous, highly motivated, and keen to develop as independent researchers at the interface of epidemiology and genomics. Before you Apply   Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.    How to Apply   To be considered for this project you MUST submit a formal online application form – on the application form select PhD Genomics Programme. Full details on how to apply can be found on the Website: How to apply for postgraduate research at The University of Manchester   If you have any queries regarding making an application please contact our admissions team FBMH.doctoralacademy.admissions@manchester.ac.uk    Equality, Diversity and Inclusion    Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website: Equality, diversity and inclusion (EDI | Postgraduate Research | Biology, Medicine and Health | University of Manchester Funding Notes Applications are invited from self-funded students. This project has a Band 1 (low) fee. Details of our different fee bands can be found on our website https://www.bmh.manchester.ac.uk/study/research/fees/  References Suzuki K […] Morris AP. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. 2024ordoff M […] Morris AP, Bowes J. Integration of genetic and clinical risk factors for risk classification of uveitis in patients with juvenile idiopathic arthritis. Arthritis & Rheumatology. 2024Morris AP, Zeggini E. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genetic Epidemiology. 2010Zhao SS […] Bowes J. Genetically proxied interleukin-13 inhibition is associated with risk of psoriatic disease: Mendelian randomization study. Arthritis & Rheumatology. 2024Zhao SS […] Bowes J. Association of lipid-lowering drugs with risk of psoriasis: a Mendelian randomization study. JAMA Dermatology. 2023 Apply Now

Using genetic risk scores to improve diagnosis and outcomes in seronegative inflammatory arthritis

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Details Diagnosing inflammatory arthritis promptly and accurately can be challenging when antibody blood tests are normal (“seronegative”) and clinical features overlap. Seronegative rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis and polymyalgia rheumatica can present with similar symptoms but require different treatment strategies. Misclassification can lead to delayed effective treatment, prolonged glucocorticoid exposure and poorer outcomes. This PhD will use large-scale linked clinical and genomic datasets, including biobank and disease-specific cohorts, to test whether polygenic risk scores for rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis can improve disease classification, prognosis and treatment stratification. The project comprises three complementary studies. Study 1: Genetically informed stratification of axial spondyloarthritis The student will examine whether axial spondyloarthritis and psoriatic arthritis genetic risk distinguishes clinically meaningful subgroups within axial spondyloarthritis. Analyses will focus on clinical phenotype, extra-musculoskeletal manifestations, disease severity, treatment response and drug persistence, with the aim of supporting more personalised management and treatment selection. Study 2: Genetic classification of seronegative rheumatoid arthritis Seronegative rheumatoid arthritis is an underserved patient group, often experiencing longer diagnostic delays and less intensive treatment than seropositive rheumatoid arthritis. The student will test whether polygenic risk scores for rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis distinguish subgroups with different disease severity, treatment outcomes or later diagnostic reclassification. Study 3: Genetic risk and steroid outcomes in polymyalgia rheumatica The student will identify people with polymyalgia rheumatica using linked primary care and prescribing data. They will test whether higher genetic liability to rheumatoid arthritis, psoriatic arthritis or axial spondyloarthritis is associated with prolonged glucocorticoid treatment or later diagnostic reclassification, potentially identifying patients whose apparent polymyalgia rheumatica reflects overlapping inflammatory arthritis biology. The student will receive training in polygenic risk scores, electronic health record phenotyping, large-scale linked datasets, and longitudinal/prediction modelling. They will gain experience working across genetic epidemiology, clinical rheumatology and precision medicine, supported by an interdisciplinary supervisory team with expertise in inflammatory arthritis, genomics and real-world data. This project will prepare the student for a career in genetic epidemiology, precision medicine, rheumatology research, health data science, biotechnology or pharmaceutical research. Eligibility   Candidates should hold, or be close to obtaining, a first-class or strong upper second-class honours degree, or equivalent, in a relevant quantitative, biomedical or population health discipline. Suitable backgrounds include epidemiology, biostatistics, bioinformatics, statistical genetics, data science, computational biology, public health, genetics, medicine or a related field. We particularly encourage applications from candidates with strong quantitative aptitude, experience using statistical software such as R or Python, and an interest in applying large-scale health and genomic data to clinically important questions in inflammatory arthritis. Prior experience with epidemiological analysis, regression modelling, electronic health record data, polygenic risk scores, longitudinal analysis, prediction modelling or pharmacoepidemiology would be advantageous. Candidates should be intellectually curious, methodologically rigorous, highly motivated, and keen to develop as independent researchers at the interface of epidemiology, genomics and precision medicine. Before you Apply   Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.    How to Apply   To be considered for this project you MUST submit a formal online application form – on the application form select PhD Genomics Programme. Full details on how to apply can be found on the Website: How to apply for postgraduate research at The University of Manchester   If you have any queries regarding making an application please contact our admissions team FBMH.doctoralacademy.admissions@manchester.ac.uk    Equality, Diversity and Inclusion    Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website: Equality, diversity and inclusion (EDI | Postgraduate Research | Biology, Medicine and Health | University of Manchester  Funding Notes Applications are invited from self-funded students. This project has a Band 1 (low) fee. Details of our different fee bands can be found on our website https://www.bmh.manchester.ac.uk/study/research/fees/  References Zhao SS […] Bowes J. Genetically proxied interleukin-13 inhibition is associated with risk of psoriatic disease: Mendelian randomization study. Arthritis & Rheumatology. 2024Zhao SS […] Bowes J. Association of lipid-lowering drugs with risk of psoriasis: a Mendelian randomization study. JAMA Dermatology. 2023Suzuki K […] Morris AP. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. 2024Tordoff M […] Morris AP, Bowes J. Integration of genetic and clinical risk factors for risk classification of uveitis in patients with juvenile idiopathic arthritis. Arthritis & Rheumatology. 2024Morris AP, Zeggini E. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genetic Epidemiology. 2010   Apply Now

Designer photoenzymes for selective C-H functionalisations

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Details A PhD studentship is available in the groups of Dr Florence Hardy and Prof Anthony Green, University of Manchester, as part of the cross-institutional BioAID Doctoral Training Programme, including world-leading experts from Queen’s University Belfast, University of Manchester, University of Edinburgh and University of Bristol. BioAID will train the next generation of scientists in Artificial Intelligence and data-driven approaches for translational biocatalysis, addressing critical needs in the development of sustainable biotechnologies. The programme will equip PhD students with advanced expertise in enzyme science, machine learning, enzyme engineering and synthetic biology, accelerating innovation across sections including pharmaceuticals, agri-tech and clean manufacturing. Students will undertake interdisciplinary, co-supervised projects across biocatalysis and AI, supported by national computing infrastructure, hands-on laboratory training, and strong academic/industry partnerships through co-designed projects and placements. In addition, students will benefit from structured cohort training and tailored professional development delivered by partner institutions. Project Summary: This studentship will focus on designing photoenzymes for enantioselective C-H functionalization chemistry using the latest deep learning tools for protein design. Non-selective photo-chemical methods for C-H heteroarylation have been established using di-aryl ketones as a photosensitiser; however, enantioselective versions of these processes remain elusive. Inspired by these studies, we will design photoenzymes to catalyse the 4-pyridination of benzylic Csp3–H bonds. To achieve this goal, we will use advanced computational enzyme design techniques to develop custom proteins that accommodate genetically incorporated photocatalytic moieties and substrate binding pockets to create ideal chiral environments for promoting enantioselective C-C bond forming chemistry. Through this project, the student will receive training across a range of cutting-edge disciplines and gain expertise in the latest tools for enzyme design and protein structure prediction, organic synthesis, biocatalysis, and directed evolution. The successful candidate will join a growing team of researchers, housed within the Manchester Institute of Biotechnology (MIB) at the University of Manchester. Enquiries can be directed to the supervisors. Eligibility The scheme is open to UK students. · Fulfil The University of Manchester entry requirements  · Hold (or expect to achieve) a First Class or 2:1 UK honours degree (or international equivalent to be checked with UoM admission team). · Ideally hold a master’s-level qualification at merit or distinction (or international equivalent to be checked with UoM admission team). · Demonstrate willingness to travel to partner institutions to complete the programme. · Fulfil the Faculty of Science and Engineering Postgraduate Researcher person specification Before you apply We strongly recommend that you contact the supervisors for this project before you apply florence.hardy@manchester.ac.uk How to apply To be considered for this project you’ll need apply here: In your application, include the project title Designer photoenzymes for selective C-H functionalisations, supervisor Dr Florence Hardy. Select the PhD Chemistry in the programme detail section and include contact details of two referees. Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.  If you have any queries regarding making an application please contact our admissions team FSE.doctoralacademy.admissions@manchester.ac.uk Equality, diversity and inclusion Equality, diversity and inclusion are fundamental to the success of The University of Manchester, and are at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.  We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.  We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder). Funding Notes This 4-year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026. We recommend that you apply early as the advert may be removed before the deadline.  References Crawshaw, R. et al. (2025) Efficient and selective energy transfer photoenzymes powered by visible light. Nature Chemistry 17, 1083–1090Lister, T. et al. (2025) Engineered enzymes for enantioselective nucleophilic aromatic substitutions. Nature 639, 375–381 Apply Now

Research Associate in Cancer Microbiology

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About the role Applications are invited for a 3‑year postdoctoral research position to work within the Host–Microbe Co–Metabolism group at the MRC Laboratory of Medical Sciences (LMS)/Institute of Clinical Sciences, in close collaboration with partners at Imperial College London. The microbiome plays a pivotal role in shaping host physiology, with emerging evidence linking microbial communities and their metabolites to cancer initiation, progression, and therapy response. Microbiota‑derived signals can influence key pathways involved in inflammation, metabolism, immune modulation, and cellular proliferation, yet the underlying mechanisms remain poorly understood. The successful candidate will employ molecular and quantitative approaches, using conventionally raised and germ‑free mouse models, to dissect how microbial composition, function, and metabolite production shape tumour initiation, progression, and therapeutic response. For more information, please visit https://www.cabreirolab.org or contact (fcabrei@ic.ac.uk). What you would be doing The successful candidate will use state‑of‑the‑art mouse models (including germ‑free and gnotobiotic systems), in combination with genome engineering, microbiology, and multi‑omics profiling, to uncover microbiome–host interactions that drive cancer‑relevant phenotypes. You will design and implement mechanistic studies to define how specific microbial communities and metabolites modulate host pathways controlling tumour growth, therapy response, and microenvironmental cues. Working closely with wet‑lab scientists, bioinformaticians, and clinicians, you will integrate quantitative phenotyping, bulk and single‑cell profiling, and microbial manipulation to reveal conserved principles of host–microbe co‑metabolism in cancer biology. You will also be encouraged to contribute to related projects within the Host–Microbe Co‑Metabolism group and to help shape new research directions at the interface of microbiome research, cancer biology, and systems biology. What we are looking for A PhD (or equivalent) in a relevant field such as cell biology, microbiology, cancer biology, or a related discipline. Strong research experience with organismal systems, ideally including mouse models, and a demonstrated interest in host–microbe interactions. Proven expertise in core molecular and cellular biology techniques, and experience in studying signalling pathways relevant to cancer, metabolism, or immunity. Experience working with complex datasets (e.g. multi‑omics, imaging, or quantitative phenotyping) and an interest in applying integrative or quantitative approaches. Good knowledge of experimental design, statistics for biological data, and reproducible workflows. Evidence of independence, excellent communication skills, and the ability to work collaboratively within multidisciplinary teams. Flexibility to work abroad to conduct animal studies. What we can offer you The opportunity to work at the cutting-edge of human mechanistic and translational research in a vibrant and supportive environment. You will be encouraged to contribute to other projects within the Cabreiro team. There are excellent opportunities for professional development – taking full advantage of collaborations, facilities and informatics expertise across MRC LMS and Imperial College London. We will provide training and mentoring to support your career aspirations. The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity. Grow your career: Gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes). Further information This is a full-time, fixed-term post for 3 years. For further information about this role, please contact Filipe Cabreiro (f.cabreiro@lms.mrc.ac.uk).  Available documents Attached documents are available under links. Clicking a document link will initialize its download. download: Employee Benefits Booklet – V.2026.pdf download: Job Description Research Associate in Cancer Microbiology .pdf Apply Now

Research Associate in Salmonella clinical study

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About the role Are you an enthusiastic, organised person with experience working within clinical trials, expertise in immunology and an interest in the human microbiome?. We are looking for a motivated Research Associate to join a small team carrying out a type of clinical trial called a human challenge study, to better understand protective immunity to Salmonella typhimurium infections. The focus of the role is how immune responses are shaped by the host microbiome and associated multi-omic signatures. What you would be doing This is an exciting opportunity to join a vibrant, growing infectious disease research group at Imperial led by Dr Malick Gibani (weblink). The post is funded by a Wellcome Trust Discovery Award to investigate mechanisms of colonisation resistance to Salmonella. You will work as part of a team of clinical staff and research scientists and with multidisciplinary investigators and postdoctoral researchers across partner institutions to help deliver the study. Your role will include laboratory work (including processing blood and stool samples from trial participants following strict SOPs, RNA/DNA extraction, ELISAs, multiplex cytokine assays, and flow cytometry) and in silico work (integrating clinical phenotypes with immunology and microbiome datasets). This post is an excellent opportunity to use your previous experience in research to help shape the future of vaccine research for Salmonella Typhimurium. What we are looking for We are looking for applicants with a relevant PhD (or near completion), and solid experience working in a research laboratory and within clinical trial environments. A developed knowledge of microbiology and the microbiome is also desirable. *Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £43,863 – £47,223 per annum. You will also need: The ability to bridge wet-lab immunology with computational analysis A record of publication in peer-reviewed journals Knowledge of Good Clinical Practice (GCP) Experience in a breadth of relevant research methods and statistical procedures Sound knowledge of immunology and microbiology Strong communication skills and team-working abilities Excellent organisational skills and attention to detail Ability to prioritise tasks and manage your own time effectively Be supportive of all team members and always demonstrate a positive attitude What we can offer you Join as a valuable member of an exciting research group at Imperial The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity. Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression. As a member of research staff you have 10 development days to use to develop your skills and explore your career prospects Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing. Further information This is a full-time post (35 hours per week) for a fixed-term contract for up to 36 months. The research group is based within the Department of Infectious Disease in the Department of Medicine at Imperial College London. It is located mainly at South Kensington Campus, although it will be necessary to work in other campuses (Charing Cross and Hammersmith) where laboratory facilities are available. Hybrid working is permitted according to Imperial College guidance. Should you require any further details on the role, please contact Dr Malick Gibani (m.gibani@imperial.ac.uk). Available documents Attached documents are available under links. Clicking a document link will initialize its download. download: Research Associate in Salmonella Clinical Study JD.pdf download: Employee Benefits Booklet.pdf Apply Now

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