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The Leibniz-Institut für Wissensmedien (IWM) conducts research into the acquisition and sharing of knowledge and cooperation with digital media. The institute is a member of the Leibniz Association
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 3 months ago
the Center, and they will contribute their skills and knowledge to other projects in the Center and to the MPIDR. We are seeking creative, self-driven, and collaborative scholars. Good knowledge
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structure- and ligand-based drug design methods (e.g., docking, QSAR, classic molecular dynamics, etc.) Familiar with all aspects of protein-ligand interactions. Solid python programming knowledge and good
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doctoral degree in psychology, cognitive science, biology, computer science, medicine or an equivalent discipline Relevant research experience or interest in the field of “Decision Neuroscience
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for physics and materials science applications scenarios as well as for related research data management tasks Developing LLM-driven agents that integrate domain knowledge to support structured chain-of-thought
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this knowledge, develop them as minimally invasive neural devices. Specifically, we aim to develop a toolbox of nanomaterials to study and learn from, looking at e.g. how nanoelectrode size and shape affects
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package Good communication skills in English (knowledge of German is not necessary) We offer Target-oriented individual further education and training opportunities Targeted training on the job Ticket for
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degree with subsequent PhD in Physics, Chemistry, Material Science or related disciplines Profound knowledge of the structural characterization of matter primarily with neutron and X-ray scattering
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environment (e.g. cleanroom, laboratory Deep knowledge of solid state physics and/or quantum information Experience with microfabrication and/or operating and calibrating quantum systems Experience with
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, Mathematics, Physics, or similar fields Broad interest in scientific topics Good knowledge of AI and applied Machine Learning Practical experience with High Performance Computing Systems as well as parallel