Postdoctoral Researcher in Computational Genetics

European Molecular Biology Laboratory (EMBL); Deutschland; Vor Ort; EUR 50.000 - 65.000; Vollzeit

Zusammenfassung

A leading cell biology research institute seeks a postdoctoral researcher to join a collaborative project focused on developing computational methods to investigate effects of rare genetic variants. The position offers the opportunity to work closely with GSK scientists on impactful research in genomic technologies, contributing to advancing understanding of human traits through computational biology.

Leistungen

Monthly family and child allowances

Generous stipend reviewed yearly

Private medical insurance

30 days annual leave

On-site library and gym

Qualifikationen

• PhD or similar in relevant fields required.
• Experience in machine learning and statistical modeling.
• Strong programming skills in Python.

Aufgaben

• Develop computational methods to study rare variants.
• Collaborate on population-scale cohort studies.
• Work with GSK scientists in research settings.

Kenntnisse

Statistical learning

Machine learning

Programming in Python

Bayesian inference

Deep learning

Ausbildung

PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering

Tools

PyTorch

Keras

TensorFlow

Jobbeschreibung

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 and the AI Health Innovation Cluster).

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. This project builds on the recently published DeepRVAT framework, which leverages advances in machine learning to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend time working with GSK scientists and in GSK research compute environments, ensuring this work has immediate application to the research activities in Genomic Technologies at GSK.

Possible directions within this project include:

• Extending DeepRVAT towards non-coding genetic variation

• Applying DeepRVAT to population-scale single-cell readouts

• Integrating population data with experimental 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 may also have

• Expertise in biological data science and data-driven discovery, scientific programming and genetic analysis. We encourage applications also from candidates with little background in biology or medicine, and a keen interest to learn.
  

Recent publications:

• 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

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 insurancefor 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
  

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 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. 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

13/07/2025

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