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A leading research institution in Germany is seeking a Research Group Leader to lead a team focusing on AI applications to biology. This role involves developing cutting-edge research programs and fostering interdisciplinary collaboration. Candidates should have a PhD, strong research background in AI, and a compelling future research plan. The position offers generous funding, a collaborative environment, and extensive resources for innovative research.
Are you ready to lead groundbreaking research in AI for Biology? Join us at EMBL! We are seeking a visionary scientist to establish their own independent research group bridging innovations in machine learning/AI with modern biology at the AI Hub Heidelberg as part of EMBL AI, a major institutional initiative to embed AI across all areas of life sciences. EMBL provides a unique environment for young scientists to conduct groundbreaking research and technology development across the life sciences.
About us
EMBL AI is EMBL's ambitious new initiative aiming to exploit the full potential of AI-based approaches to advance scientific discovery. EMBL AI will host new AI research groups and data engineering teams, supported by state-of-the-art infrastructure, along with fellowship and skills development programmes that bridge AI and life sciences. EMBL AI groups will be embedded in a world-class environment of biological researchers covering a broad range of biological areas, from molecules to ecosystems. EMBL has established itself as a global leader in AI-driven innovation in biology research, with successes in areas including genomics, structural biology (e.g., AlphaFold), biomarker discovery, and imaging. EMBL hosts the world's largest repository of biological data, the European Bioinformatics Institute (EMBL-EBI), and has excellent pan-institutional data management, data science and open science infrastructures. Our goal is to build a dynamic community of AI specialists working alongside life science researchers, together creating innovative AI-based methods to address fundamental questions in biology and drive scientific breakthroughs.
Scientific context and strategic fit
EMBL's long-term scientific direction, Molecules to Ecosystems, aims to advance our understanding of ecosystems at the molecular level, applying expertise in molecular biology to study life in its natural context. Research areas include applying experimental, computational and theoretical approaches to study how cells and organisms interact with each other and respond to fluctuating environments. EMBL has a track record in establishing landmark data resources in these different areas (EMBL-EBI), leads in managing digital infrastructures, and operates a dedicated Data Science Center for handling complex primary biological data types across the institute. We are interested in hosting scientists who can enhance these biological areas using AI-based approaches and technological innovations. We welcome proposals that integrate ML/AI with model-driven experimentation, lab automation or study sampling, as well as those that advance machine learning methodology and theoretical concepts. Possible research areas include: machine learning foundations, generative modelling, foundation models, cross-domain/-modality learning, explainable AI and mechanistic interpretability, representation learning, Bayesian inference, causal inference, active learning, AI-based agents in the scientific process. You will use AI to enhance biological discoveries in any area of biology.
Incoming groups will collaborate with scientists across EMBL's scientific units, sites and cross-cutting research topics, and have access to biodata, biotechnologies, and expertise in biological research. Example topics for interactions with the scientific units in Heidelberg include multi-modal data integration towards whole-cell models, prediction of protein function and protein-ligand interactions, regulatory networks, single-cell and spatial omics, precision medicine, multi-scale models in space and time for organelles and cells, or collectives of unicellular and multicellular organisms.
Your role
You will:
Your profile
You should have an exciting research plan for your future team. You have an excellent research record in AI, a PhD in a relevant field, and an interest in AI applications to biology. Previous experience in biology is not required, but a strong interest in interdisciplinary collaboration is essential.
Key competencies
Why EMBL is an excellent environment for you to become a Research Group Leader
EMBL typically appoints group leaders early in their career and provides everything you need to support this transition to your first independent position to achieve your research goals. EMBL group leaders benefit from:
Online interviews will be conducted in November 2025. Onsite interviews are planned for January 2026.
Contract length: 5 years, renewable to a maximum of 9 years.
Salary: Grade 9, monthly salary from EUR 6,659.04 (before taxes and EMBL social security deductions) plus other paid benefits.
Further information on Group Leader appointments can be found here: https://www.embl.org/careers/group-leader-recruitment/
How to apply
Before applying, please read the application instructions here. Submit an exciting research plan with original and ambitious goals for your future team (maximum 4 pages). In your online application, include a cover letter, your CV, the names and contact details of 2 referees, and a concise description of research interests & future plans highlighting your unique vision (up to four pages). Letters of recommendation should be submitted by the referees by or shortly after the application deadline.
Why join us
EMBL is curiosity-driven, community-oriented and international. We are an inclusive, equal opportunity employer, committed to creating an inclusive and flexible culture. We actively encourage applications from all genders and cultures, ethnic groups and all demographics to reflect the diversity of the populations our science serves.
Benefits
What else you need to know
Closing Date
02/11/2025