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to predict bacterial growth from protein sequence and compound molecular structure. Applying generative and predictive models to propose novel compounds optimized for broad-spectrum activity against diverse
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Python and common deep learning frameworks (PyTorch) • Excellent communication skills in English (German is a plus) • Independent, structured working style and experience in supervising students Preferred
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a period of 2 years (extendable with 1 year); Access to cutting-edge computing infrastructure as well as motion capture scanning facilities. Structured support for your next career steps, whether in
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practices, organisational structures, and existing infrastructures. Building on insights from ethnographic studies of robot use in healthcare, which have shown how human-robot collaboration is shaped by
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the binding locations of various proteins within the nuclear pore complex (NPC), the locations of various transport pathways though the pore, and the structural and dynamic properties of the FG
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. Perform research by integrating tools from protein engineering, e.g. phage display, yeast display, high-throughput screening and structure-based protein design, with those applied in virology, bacteriology
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Job Description Are you interested in contributing to the development of digital twin software for additive manufacturing (AM) of large-scale fibre composite structures? If so, the Department
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grant-funded position involves conducting research through multidisciplinary approaches to investigate host immunity to pathogens, bacterial physiology, structural biology, macrophage biology, host
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colloidal routes, enabling precise control over size, morphology, composition, and structural complexity. This role offers an unparalleled opportunity to lead the computational core of a cutting-edge
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Subject description The Center for Molecular Protein Science (CMPS), Department of Chemistry brings together scientists active within the fields of biochemistry, molecular biophysics, structural