For ‘dry-lab’ bioinformaticians, we offer opportunities to develop applied projects based on our own experimental data, data from collaborators at EMBL and outside, and projects focused on software development. For ‘wet-lab’ experimentalists, we have a cell biology lab, in which we run proteomics and imaging projects related to the influenza A virus.
We have three post-doctoral positions available within the ERC Synergy Grant with Julia Mahamid (EMBL Heidelberg), Juri Rappsilber (TU Berlin), and Rachel Green (Johns Hopkins University). Official job ads will open soon, but please contact Jan Kosinski now by email if you are interested. We also have two PhD positions available, one from the above ERC grant.
Your role: Develop new computational methods for modeling the atomic structure of large macromolecular complexes by leveraging tools like AlphaFold and RoseTTAfold, your own new AI-based algorithms, and integrating experimental data from in-cell cryo-electron tomography and crosslinking. You have: Ph.D. in Computer Science, Computational Structural Biology, or a related field; Strong programming skills in Python; some machine learning experience. Duration: 3-5 years. Fully funded.
In collaboration with, and AI co-mentoring by, Fabian Theis at Helmholtz Münich.
Your role: Develop new computational methods to mine electron tomograms and cryo-ET maps, aiming to identify macromolecular complexes in tomograms with higher precision and completeness. To achieve this, you will employ advanced image processing methods and incorporate complementary experimental data from crosslinking, as well as structural models from tools like AlphaFold. In the long term, your efforts will contribute to redefining cryo-ET data mining as an integrative structural modeling challenge. You have: Ph.D. in Computer Science, Image Processing, Computational Structural Biology, or a related field; Strong programming skills in Python. Duration: 3-5 years. Fully funded.
Your role: Apply in-cell cryo-ET to study how translational machinery changes upon influenza A virus infection. You will use our superb cryo-EM and ALFM facilities and leverage our established pipeline for cryo-ET of cells infected with the virus. You have a Ph.D. in structural biology and experience in cryo-electron tomography. Duration: 3-5 years
Your role: Develop and apply new methods for modeling protein-protein interaction networks. Integrate AI-based structure prediction, experimental structure, and data from cross-linking mass spectrometry. Further extend AlphaPulldown program. Develop new AI-based algorithms. You have: an education in Computer Science, Computational Structural Biology, or a related field. Experience in machine learning. Duration: 3.5-4 years. Fully funded.
Your role: In-cell cryoET and/or crosslinking mass spectrometry in the context of influenza virus infection. You have: an education in Molecular Biology, Structural Biology, or a related field. Internships in molecular cell biology. Duration: 3.5-4 years. Fully funded.
Applicants interested in other subjects and willing to apply for external fellowships are always encouraged to contact Jan Kosinski by email.
We are always looking for students to work in either dry lab, on developing and applying novel computational methods, or wet lab, on experimental molecular cell virology projects. For dry lab, a background and/or interest in bioinformatics, structural modeling, programming, image analysis, or systems biology is beneficial. Students will have the opportunity to learn a variety of bioinformatics and modeling tools and gain expertise in the cutting-edge field of integrative structure and systems biology. For the wet lab, experience in mammalian cell culture would be strongly beneficial. Students are expected to be highly motivated to work on challenging research projects in an international team.