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novel machine learning-guided approaches. The position is located at TUM Campus Heilbronn. Your qualifications Strong background in computer science, AI, or related areas or similar fields. Solid
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
, Applied Mathematics, Physics, Biophysics or a similar qualification Interest in and/or experience with AI/machine learning A willingness to learn and extend this knowledge and master new challenges in
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
biological samples' 3D structure and molecular identity. At iBIO, we bring together cutting-edge science from biology, chemistry, engineering, and computer applications. Our overarching aim is to obtain a
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Field of study: computer science, mathematics, software design, software engineering, technical computer science or comparable. Machine Learning (ML) models are reaching a maturity level that allows
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pursuing a Bachelors or Masters degree in engineering, physics, mathematics or computer sciences and related discipline and/or an unaffiliated recent graduate with a Bachelor/Master degree from
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advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target areas are drug
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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biological samples' 3D structure and molecular identity. At iBIO, we bring together cutting-edge science from biology, chemistry, engineering, and computer applications. Our overarching aim is to obtain a
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High