Location: Hamburg, Germany
Staff Category: Postdoctoral Fellow
Contract Duration: 3 years with possibility of extension up to 5 years
Grading: Competitive Postdoctoral Fellowship

Please apply by sending the cover letter and CV to Jan Kosinski <jan.kosinski@embl.de>

The Jan Kosinski group at EMBL Hamburg and the Fabian Theis group at Helmholtz Münich seek a Postdoctoral Fellow to employ AI methods for the integrative structural modeling of macromolecular complexes. This position is part of the TransFORM consortium, funded by the prestigious ERC Synergy Grant, which aims to map the intricate workings of protein translation machinery in human cells using cutting-edge cryo-electron tomography, mass spectrometry, and computational modeling of atomic structures.

Your role

Despite the emergence of AlphaFold and related AI-based modeling tools, large macromolecular complexes still cannot be consistently modeled with high accuracy. Experimental data can guide the modeling of large complexes; however, methods for modeling based on experimental data are not sufficiently automated, computationally inefficient, and lack general applicability. To address this, you will:

• Develop computational methods to model the atomic structure of large macromolecular complexes using tools such as AlphaFold, RoseTTAfold, and OpenFold, alongside your own innovative AI-based algorithms, and integrating experimental data from in-cell cryo-ET tomography and crosslinking mass spectrometry
• Investigate and implement methods that combine statistical techniques like Bayesian inference and Monte Carlo sampling with non-linear optimization approaches and advanced deep learning (e.g., geometric deep learning and reinforcement learning).
• Contribute to open-source codebases such as OpenFold, AlphaPulldown, and Assembline
• Disseminate your code in well-organized, documented, and rigorously tested software packages
• Use these new methods for research projects within the TransFORM consortium.

You will be affiliated with the research group of Jan Kosinski at EMBL Hamburg, but you will spend at least a year as a visiting postdoctoral fellow at the Fabian Theis group at Helmholtz Münich.

You have

• Ph.D. in Computer Science, Computational Structural Biology, or a related field
• Experience in deep learning
• Experience with machine learning techniques and frameworks, including Scikit-learn, TensorFlow, PyTorch, or JAX
• Proficiency in numerical libraries such as NumPy and SciPy
• Experience in the dissemination and management of software packages
• Strong motivation to work in a highly collaborative and multidisciplinary environment of EMBL, Helmholtz Münich, and the TransFORM consortium

You might also have

• Experience in computational structural modeling. However, candidates with a strong background in either computer science and a willingness to learn structural biology are encouraged to apply.
• Experience in deep learning techniques that can be applied for modeling or analysis of 3D macromolecular structures, such as geometric deep learning, graph neural networks, transformer and attention-based models, and reinforcement learning.

Why join us

The Kosinski group has an excellent track record in computational modeling of the atomic structure of biological macromolecules, while the Theis group is renowned for applying AI to complex biological problems. With us, you will find the perfect balance between academic research and software development, supported by a competitive academic salary and benefits. You will engage in exciting scientific projects within a creative environment, collaborating with research groups that regularly publish in top-tier journals such as Nature, Science, Cell, Nature Methods, and Nature Protocols. Your computational tools will have wide applications in the emerging field of in-cell structural biology. You will have access to high-quality unpublished experimental data and computing resources, including high-end server GPUs. Simultaneously, you will enhance your algorithm and software development skills, preparing you for a career in either academia or industry.

EMBL is curiosity-driven, community-oriented and international. As an inclusive, equal opportunity employer, we believe that diversity enables us to collaborate more effectively and be innovative in our approaches. We are, therefore, committed to creating an inclusive and flexible culture – one where everyone can realise their full potential and make a positive contribution to our organisation.

We encourage applications from individuals who can complement our existing team – we believe that success is built on having teams whose backgrounds and personal experiences reflect the diversity of the populations that our science serves. We actively encourage applications from all genders and cultures, ethnic groups and all demographics to help us avoid perpetuating biases and oversights at this transformational point in our people strategy.

EMBL offers attractive conditions and benefits appropriate to an international research organisation with a very collegial and family-friendly working environment. Competitive salary and social security benefits, financial support for relocation, a relaxed culture, professional development, and other staff facilities make EMBL a great place to work.

** 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.

What else you need to know

We are Europe’s research laboratory for the life sciences – an intergovernmental organisation performing scientific research in disciplines including molecular biology, physics, chemistry and computer science. We are an international, innovative and interdisciplinary laboratory with more than 1900 employees from many nations, operating across six sites, in Heidelberg (HQ), Barcelona, Hinxton near Cambridge, Hamburg, Grenoble and Rome.

Our mission is to offer vital services in training scientists, students and visitors at all levels; to develop new instruments and methods in the life sciences and actively engage in technology transfer activities, and to integrate European life science research. The working language of the institute is English.

EMBL is a signatory of DORA. Find out how we implement best practices in research assessment in our recruitment processes here.