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Scientific Personnel 05.03.2026, Academic staff BioSysteM Cluster of Excellence at TUM invites applications for a Postdoctoral Researcher (m/f/d) to lead and further develop the Protein Design
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Postdoc (f/m/d) on Generative AI for de Novo Protein Design / Completed university studies (PhD) ...
Area of research: Scientific / postdoctoral posts Starting date: 01.02.2026 Job description: Postdoc (f/m/d) on Generative AI for de Novo Protein Design With cutting-edge research in the fields
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Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf | Germany | about 2 months ago
for de Novo Protein Design. Your tasks Design of generative AI models (e.g., VAEs, GANs, Diffusion Models) to create novel protein sequences, fold structures, and functional molecules Engage with our
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 2 months ago
Job description:Postdoc (f/m/d) on Generative AI for de Novo Protein Design With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70 nations
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Your Job: Design and development of a modular high throughput sample environment for chemical hydrogen storage investigations under realistic conditions Design, optimization, and testing of sample
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new topics while playing nice in a team. Your main task will be the development, conceptualization, and eventual implementation of new design automation methods and software for your field, e.g
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universities, the Helmholtz Zentrum München and the Max Planck Institute of Biochemistry, collaborate on an interdisciplinary basis. The cluster's research vision is to design and control biological systems
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members. The DKFZ is a place where the brightest minds pursue bold ideas and seek answers to pioneering scientific questions through collaboration, innovation, and exploration across many disciplines. We
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technology Preparation and support of the work by evaluating relevant technical literature and new developments Design and production of systematically varied compounds and test specimens Design and
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representations • Research on multimodal representation learning for fusing heterogeneous clinical data (imaging, pathology, genomics, clinical text) into unified vector representations • Design and evaluation