Postdoctoral Researcher in Computational Genetics

The research group of Oliver Stegle looks for a postdoctoral researcher to join a collaborative project with GSK with the goal to apply computational methods to investigate the effects of rare variants on human traits and single-cell readouts.
 

Our research group is pioneering computational methods for deciphering molecular variation across individuals, space, and time. We have a track record in the development of computational methods for genetics, high-throughput omics data and causal discovery. Our interdisciplinary and international team is jointly located at DKFZ and EMBL Heidelberg, and is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg, including ELLIS Life Heidelberg.

Your role 

You will work in an international team to develop computational methods that are designed to investigate the effects of rare variants and apply them in large cohort studies. We aim to build on prior work such as our DeepRVAT framework, an end-to-end deep learning model that leverages variant annotations to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend time working to blend working at EMBL in an academic setting with collaborations with GSK scientists, and profit from the GSK research compute environments. The specific objectives will be designed together with the incoming fellow. Possible directions include but are not limited to:

• Extending DeepRVAT towards non-coding genetic variation
• Applying DeepRVAT to population-scale single-cell omics cohorts
• Integrating population-scale scRNA-seq with genome-scale CRISPR perturbation datasets

The project can be adapted to match the qualifications and interests of possible candidates and we encourage you to apply even if you do not meet all, but some of the requirements below.

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. 

You might also have

• Expertise in biological data science and data-driven discovery, including in human genetics. We explicitly encourage applications also from candidates with little background in biology or medicine, and a keen interest to engage with this domain.

Recent publications:

• Vagiaki, Danai, et al. "Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference." bioRxiv (2026)
• Clarke, B., Holtkamp, E., et al. Integration of variant annotations using deep set networks boosts rare variant association testing. Nature Genetics (2024).
• Marconato, L. , Palla, G. , Yamauchi, K. A. , Virshup, I., et al. SpatialData: an open and universal data framework for spatial omics. Nature Methods (2024).
• Velten, Britta, et al. Identifying temporal and spatial patterns of variation from multi-modal data using MEFISTO. Nature Methods (2022).
• Kleshchevnikov, Vitalii, et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nature Biotechnology (2022).
• Argelaguet, R., et al. Multi-Omics factor analysis disentangles heterogeneity in blood cancer. Molecular systems biology (2018)

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

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 (Heidelberg), on-site library, subsidised on-site 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
   

What 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 believe that diverse teams drive innovation and scientific excellence. We encourage applications from candidates of all genders, identities, nationalities and/or any other diverse backgrounds.

• 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. Applications will close at 23:59 CET on the date shown below. We aim to provide a response within two weeks after the closing date.

Closing Date

30/04/2026