Postdoctoral Fellow – AI-Based Modeling, EMBL Hamburg, Germany

Postdoc in Germany
Postdoctoral Fellow – AI-Based Modeling: The Jan Kosinski group at EMBL Hamburg and the Fabian Theis group at Helmholtz Münich are seeking a highly motivated Postdoctoral Fellow to delve into AI methods for integrative structural modeling of macromolecular complexes. This role is a crucial part of the TransFORM consortium, funded by the prestigious ERC Synergy Grant, aiming to map the intricacies of protein translation machinery in human cells.

Postdoctoral Fellow – AI-Based Integrative Modeling of Macromolecular Complexes

Designation:

Postdoctoral Fellow

Research Area:

AI-Based Integrative Modeling, Structural Biology, Computational Modeling

Location:

EMBL Hamburg, Germany, with at least one year as a visiting postdoctoral fellow at Helmholtz Münich, Germany

Eligibility/Qualification:

  • Ph.D. in Computer Science, Computational Structural Biology, or a related field
  • Proficiency in numerical libraries such as NumPy and SciPy
  • Experience with machine learning techniques and frameworks including Scikit-learn, TensorFlow, PyTorch, or JAX
  • Experience in the dissemination and management of software packages

Job Description:

The Postdoctoral Fellow will:

  • Develop computational methods for modeling the atomic structure of large macromolecular complexes using tools like AlphaFold, RoseTTAfold, and OpenFold, coupled with own innovative AI-based algorithms.
  • Integrate experimental data from in-cell cryo-ET tomography and crosslinking mass spectrometry.
  • Investigate and implement methods combining statistical techniques such as 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 code in well-organized, documented, and rigorously tested software packages.
  • Use new methods for research projects within the TransFORM consortium.

You will be affiliated with the Jan Kosinski group at EMBL Hamburg, and you will also spend at least a year with the Fabian Theis group at Helmholtz Münich.

How to Apply:

Interested candidates should apply through EMBL Careers Page referencing HH00227. Detailed instructions and required application materials are available on the site.

Last Date for Apply:

19 August 2024


Join the EMBL Hamburg and Helmholtz Münich teams – leaders in computational biology and AI applications. Contribute to groundbreaking research with significant real-world applications in structural biology and develop your career in an inclusive, innovative, and collaborative international research environment.

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