Graduate / postdoctoral opportunities
Associate Professor Rachel Freathy is recruiting for a Wellcome Trust funded post to lead data analytical research projects that investigate the links between maternal obesity and its associated risks for pregnancy and birth.
The successful applicant will join a dynamic and supportive, multidisciplinary team to analyse large human genetics datasets of babies, mothers and fathers. We aim find out how a fetus regulates its own growth, how the mother’s in utero environment affects the fetus, and how the fetus may influence the mother. By clarifying mechanisms, this project aims to lay the foundations for future antenatal healthcare to be better targeted to women and their babies, according to their level of risk.
Professor Anna Murray has an MRC-funded, 3 year, postdoctoral fellow post, to identify potential drug targets for menopausal symptoms. Menopausal symptoms affect over 70% of women, yet have been under-researched and treatments are limited.
In this project we will use genetics to understand the physiological basis of a range of menopausal symptoms, to identify overlapping aetiology and ultimately discover potential new targets for drug therapies. We will use large genomic datasets such as UK Biobank and All of Us to generate new phenotypic variables from self-reported and primary care records, plus collecting new data in 3 population-based studies in the Southwest. We are looking for a postdoctoral researcher who either has skills in statistical genetics already, or has an aptitude for data science who would be keen learn in a really supportive environment where there is considerable expertise in the field.
Senior Research Fellow, Dr Matt Johnson is recruiting for a researcher post funded by the Leona M. and Harry B. Helmsley Charitable Trust to lead genomic data analysis projects in type 1 diabetes.
The successful applicant will join a collaborative and supportive team that includes molecular geneticists, computer scientists and consultant diabetes clinicians. The central aim of the project is to uncover new genetic pathways that underlie the development of extremely-early onset type 1 diabetes through analysis of an existing large and unique cohort of individuals diagnosed in infancy. Providing this new understanding of the genetic underpinning of this chronic autoimmune condition will pave the way for better treatments and agents to prevent or delay the onset of disease.
Professor Caroline Wright is recruiting a 3-year, MRC-funded, postdoctoral researcher to evaluate approaches to newborn screening with whole genome sequencing using large-scale population cohorts.
This collaborative research project seeks to address the question of whether and how to use whole genome sequencing to improve newborn screening for a range of treatable genetic conditions. We are seeking a talented postdoctoral associate or fellow to join our team, with experience working with large genomic datasets and an interest in rare diseases. The project will use large datasets from the UK Biobank (a population cohort of ~500,000) and the NHS Genomic Medicine Service. We will test different variant detection and gene-specific prioritisation approaches, determine the number and types of variants that would be prioritised for each condition, and evaluate the penetrance using hospital records and relevant biomarker data. Join us and make a real difference to how genomics is used to improve health!
Professors Emma Baple and Caroline Wright, with the South West Genomic Laboratory Hub team, are recruiting for several positions jointly between the University of Exeter and the NHS Royal Devon & Exeter Hospital to develop new approaches to rapid whole genome sequencing in diagnostics.
As part of a new NHS Genomic Network of Excellence in Rare and Inherited Diseases, we aim to harness new technologies to help more patients get a final diagnosis faster, improve clinical pathways and increase access to clinical trials. The Network includes NHS and University teams that have implemented the UK’s fastest diagnostic genome sequencing service, which enables life-saving early interventions for critically unwell children. We are looking for a data scientist/bioinformatician to develop new analytical pipelines for long-read sequencing data, and a genomic/clinical scientist with expertise in variant classification for rare disease. This exciting opportunity is available for 2 years in the first instance, and individuals could be employed within the NHS or University depending on qualifications. Please contact us to discuss.
Professor Inês Barroso and Professor Jonathan Mill are recruiting for a 3 year postdoctoral research fellow to perform bioinformatic analyses of genomic data as part of ongoing work to explore transcriptional and epigenetic variation in the brain. This post is available immediately for 3 years.
The successful applicant will be an experienced bioinformatician who is excited about the opportunity to use gene expression and epigenetic data from different brain cell types to interpret genetic association signals for obesity, body mass index and other metabolic traits. They will also have the opportunity to work on other genomic data including using long-read sequencing to identify DNA modifications and profile transcript diversity. The successful applicant will be based within the Genetics of Complex Traits team (working with Professor Inês Barroso) and the Complex Disease Epigenetics Group (working with Professor Jonathan Mill) in the Department of Clinical and Biomedical Sciences at the University of Exeter. We are a dynamic, interdisciplinary team including geneticists, molecular biologists, mathematicians and bioinformaticians researching the genomic basis of complex disease.
Dr Kate Ruth, Lecturer in Clinical and Biomedical Sciences is recruiting a 4 year postdoctoral researcher funded by a UKRI Frontier Research Guarantee Grant, to use genetics to understand the role of hormones in postmenopausal health.
We aim to improve understanding of how changes in sex hormone levels across life impacts health after menopause, providing biological insights to benefit healthy ageing. We will use genomic and health data from large population-based cohorts such as UK Biobank to conduct genome-wide analyses of hormones and postmenopausal disease, exploring relationships between hormones, and using genetic epidemiology to test causal relationships between hormones and health. The successful applicant will ideally have experience of genomic analyses and/or genetic epidemiology, but as part of a large, diverse and supportive complex traits genomics team, there will be opportunities for applicants from data, computation or statistics backgrounds to develop specialist skills in genomics.
Dr. Nick Owens is recruiting multiple positions laboratory and computational positions on a Wellcome Career development award to study the sequence code underlying regulatory regions in glucose regulation disorders.
We are investigating how gene regulatory defects in pancreas development and function lead to rare and common conditions including neonatal diabetes, hyperinsulinism, and type 2 diabetes. Successful applicants will join an interdisciplinary team using cutting-edge genomics approaches, data science and artificial intelligence to understand how regulatory regions control gene expression. We are investigating how sequence changes to non-protein-coding regulatory regions of the genome impact binding of transcription factors. We are using the novel technology of single-molecule footprinting with Oxford Nanopore Technologies to understand how multiple transcription factors bind in combination in differentiated cells and fetal and adult pancreatic tissue. We are combining this with data science using Bayesian models and deep learning to gain insights into how regulatory sequence changes impact function.
We are recruiting multiple positions through a separate campaign to the one above, please apply through the following adverts:
Professor Mike Weedon is recruiting for a 2 or 3 year research fellow post funded from an MRC grant to use whole genome sequencing in >1 million people to identify non-coding elements associated with diabetes and related traits across ancestries.
Whole genome sequencing data on over a million individuals will be becoming available over the next year. We are looking for a research fellow with strong computational skills that can help us take advantage of this unprecedented amount of human genetic data. The successful applicant will use this data to make a major advance in our understanding of the non-protein coding variants that explain most of the genetic component of complex disease. We have had success in identifying non-coding regulatory mutations causing monogenic disease. This project will break new ground by using whole genome sequencing data from >1 million individuals, non-coding regulatory maps and new statistical and computational methodologies to identify rare non-coding variants and regions associated with type 2 diabetes and related traits. These will advance our understanding of the biology of Type 2 diabetes, allow us to uncover causal variants from GWAS loci, and provide insights into the regulatory elements important in the development and maintenance of beta-cells. Through analysis of patients with monogenic diabetes patients the successful applicant will help improve diagnosis and treatment of patients.