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learning, AI, or statistical modeling. Proven ability to handle large and complex datasets, including preprocessing and integration. Strong programming skills (e.g., Python, R, MATLAB, or similar
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explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment, collaborating with leading experts in AI, mathematics
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focus on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid
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on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid state
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focus is the interplay of these factors with mitochondrial translation systems and respiratory chain complex assembly. We use the yeast Saccharomyces cerevisiae as our primary research model. In
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Worldwide R&D Projects. Previous experience in one or preferably more topics from these areas is considered a merit: -Risk-aware navigation strategies that integrate visual-language models for autonomous
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and complex information spaces, for example in biochemistry, humanities, or software engineering. Our vision is to attack the big data challenge by a combination of human-centered data analysis and
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, troubleshoot complex data issues, and critically evaluate model performance. Excellent communication abilities are required to convey findings to both technical and clinical audiences, write manuscripts, and
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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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compartments including single cell- or bulk sorted immune cells and extracellular vesicles from the lung of the patient cohort, as well as from cell culture model systems. The studies are performed in close