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and Reliable Artificial Intelligence to be occupied starting from the 01.10.2022. The Trustworthy and Privacy-Preserving AI Group (PI: PD Dr. Georgios Kaissis) at the Institute for AI in Medicine
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to integrate heterogeneous molecular data, but are often less explicit about biological directionality and causal inference. This project instead builds on the structure of the central dogma, using genetic
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Experience in LLMs and developing LLM-based methods is an advantage Programming skills, ideally in Python Structured, analytical, and independent working style Reliability, attention to detail, and enjoyment
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PhD Position - Operando X-ray Characterization of Catalytic Interfaces for Chemical Hydrogen Storage
). This involves recording “molecular movies”, in which experimentally atomically resolved motion pictures of the reactions are recorded, including the structural and chemical identification
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
how can we extract it reliably? The Institute for Biological and Medical Imaging (IBMI) is looking for a curious and persistent PhD candidate (f/m/x) who wants to discover new biological and medical
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-surface interactions, analysis of spatial energy distributions, and determination of impacts of pulse characteristics on accuracy and surface quality. Expected outcomes include reliable ablation datasets
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 2 days ago
structures and reaction mechanisms Qualifications a Master’s degree in chemistry or a related field basic knowledge and research experience in molecular inorganic chemistry, coordination chemistry, catalysis
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07.08.2026, Academic staff The professorship of Digital Structures with Mineral Materials is looking for an enthusiastic doctoral (PhD) candidate for a project on reinforcement of 3D printed
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for electrocatalytic reactions Close collaboration with data scientists and automation specialists to develop a reliable, rapid material testing method Structured collection and linking of experimental data as a basis
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investigate how AI methods and workflows can be designed and adapted to handle large, heterogeneous EO tasks efficiently and reliably. You will develop and evaluate approaches that address the trade-offs