We are seeking a highly motivated computational biologist to join the research groups of Oliver Stegle (EMBL Heidelberg) and Roel Vermeulen (University of Utrecht) on an interdisciplinary project aimed at investigating the combined impact of the environment and genetics on human phenotypes. Set within the Human Ecosystems Transversal Theme, the postdoctoral candidate will join a highly collaborative community that aims to advance and apply computational techniques to large human cohorts to investigate the impact of environmental exposures and genetics on human phenotypes; the exposome-genome interface. The Human Ecosystems theme at EMBL aims to bridge human cohort and molecular mechanisms research to understand how the environment impacts human phenotypes. By building on advanced generative-transformer models developed for multi-disease risk prediction,this project offers an exciting opportunity to combine expertise in genomics and exposomics to understand the role of gene x environment. The research group of Oliver Stegle is pioneering computational methods for deciphering molecular variation across individuals, space, and time. The Stegle group has developed computational methods for genetics, high-throughput omics data and causal discovery. Complementary to this, The Institute of Risk Assessment Sciences (IRAS) at Utrecht University, is a leading institute on environmental epidemiology and exposome science. Roel Vermeulen’s team has a long-standing track record in environmental epidemiology with a focus on the exposome and quantitative risk modelling. You will be able to work with large datasets with high dimensional information on both the genome and exposome. Your role You will work in an international team across EMBL’s Human Ecosystems Programme and the Utrecht University in a unique project bridging human genomics and exposome research with the aim of identifying how the environment impacts human disease phenotypes. Your role will entail linking exposure map data related to physical-chemical, social and dietary factors across space and time with genetic resources in humans from population level bio-banks (e.g. UKBioBank, Lifelines). You will use new insights on exposures to identify Gene x Environment interactions in UKBioBank and expand these linkages to new and complex data sources which document exposure data longitudinally over time. The teams have in prior work also established generative transformer model for risk prediction, which you can build on and take to the next level to interpret genetics to phenotype within the internal space of the model, identifying at which point across life differences in exposure modify the baseline genetic disease risk to phenotypes of interest. You have A PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro or TensorFlow. The motivation and dedication to lead a scientific project and you are a supportive, creative and responsible team member. Willingness to travel between sites (Utrecht, Holland and Heidelberg, Germany) to enable successful collaboration. You may also have Expertise in biological data science and data-driven discovery, scientific programming and (epi)genetic analysis. We encourage applications also from candidates with little background in biology or medicine, and a keen interest to learn. Relevant publications: Moore, R., Casale, F.P., Jan Bonder, M. et al. A linear mixed-model approach to study multivariate gene–environment interactions. Nat Genet (2019). https://doi.org/10.1038/s41588-018-0271-0 Clarke, B., Holtkamp, E., Öztürk, H. et al. Integration of variant annotations using deep set networks boosts rare variant association testing. Nat Genet 56 (2024). https://doi.org/10.1038/s41588-024-01919-z Velten, B., Braunger, J.M., Argelaguet, R. et al. Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO. Nat Methods (2022). https://doi.org/10.1038/s41592-021-01343-9 Shmatko A., Jung A.W., Gaurav K. et al. Learning the natural history of human disease with generative transformers:. medRxiv. https://doi.org/10.1101/2024.06.07.24308553 Safarlou C.W., Jongsma K.R., Vermeulen R. Reconceptualizing and defining exposomics within environmental health: expanding the scope of health research. Environ Health Perspect (2024). https://doi.org/10.1289/EHP14509 Zhao, Y., Meijer J., Walker D.I., et al. Dioxin(-like)-Related Biological Effects through Integrated Chemical-wide and Metabolome-wide Analyses. Environ. Sci. Technol.(2023) https://doi.org/10.1021/acs.est.3c07588 Vermeulen R. Invited Perspective: Inroads to Biology-Informed Exposomics. Environ. Health Perspect (2022). https://doi.org/10.1289/EHP12224 Ohanyan H., Portengen L., Kaplani O., et al. Associations between the urban exposome and type 2 diabetes: Results from penalised regression by least absolute shrinkage and selection operator and random forest models. Environ Int. (2022). https://doi.org/10.1016/j.envint.2022.107592 Ohanyan H., Portengen L., Huss A., et al. Machine learning approaches to characterize the obesogenic urban exposome. Environ Int. (2022). https://doi.org/10.1016/j.envint.2021.107015 Vermeulen R., Schymanski E.L., Barabási A.L., Miller G.W. The exposome and health: Where chemistry meets biology. Science. (2020). https://doi.org/10.1126/science.aay3164 Further information Contract duration: This position is a 2 year contract, renewable to a maximum of 5 years. Don’t meet every single requirement? We are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply nevertheless. Professional development support The EMBL Fellows’ Career Service provides support and guidance to predoctoral and postdoctoral fellows across all six EMBL’s sites. Working with a dedicated Careers Advisor, this invaluable service will help you to take informed decisions about your career planning both in the short and longer term. Whether your main interest is pursuing a career path in academia, exploring opportunities in industry or exploring an independent venture, the EMBL Fellows’ Career Service with provide you with a portfolio of activities and resources to help you. To find out more please visit - EMBL-fellows-career-service Why join us Join a culture of innovation We are located on the Wellcome Genome Campus, alongside other prominent research and biotech organisations, and surrounded by beautiful Cambridgeshire countryside. This is a highly collaborative and inclusive community where our employees enjoy a relaxed atmosphere. We are committed to ensuring our employees feel valued, supported and empowered to reach their professional potential. Enjoy lots of employee benefits: Financial incentives: Monthly family and child allowances, generous stipend reviewed yearly, pension scheme, death benefit and unemployment insurances Flexible working arrangements including hybrid working patterns Private medical insurance for you and your immediate family Generous time off: 30 days annual leave per year in addition to public holidays Campus life: Free shuttle bus to and from work (Heidelberg), on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely) Family benefits: Kindergarten (Heidelberg), 10 days of child sick leave, paid maternity & parental leave, holiday clubs on campus and monthly family and child allowances Wha t else you need to know International applicants: We recruit internationally and successful candidates are offered visa exemptions. Read more on our page for international applicants. Diversity and inclusion: At EMBL, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ & individuals from all nationalities. Job location: All our fellowships are based on-site (for at least part of each week). If you are living overseas, you will receive a generous relocation package to support you. EMBL is a signatory of DORA. Find out how we apply DORA principles to our recruitment and performance assessment processes here How to apply: To apply please submit a cover letter and a CV through our online system. We aim to provide a response within two weeks after the closing date. Closing Date 01/05/2025