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from the vibrant research community around machine learning of the SCADS.AI center ( https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change
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presentation using common computer programs Ideally, strong communication skills in both German and English You are enthusiastic about learning new practical skills, approach unfamiliar topics with curiosity and
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Since 2020, Fraunhofer Heinrich Hertz Institute has worked with United Nations
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-scale controllable, and cost-efficient disease models by bringing together experts in physical chemistry, physics, bioengineering, molecular systems engineering, machine learning, biomedicine, and disease
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exploration to extract meaningful business insights. Provide analytical support to business teams, guiding strategic and operational decisions. Perform econometric analysis and machine learning tests. Draft
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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macromolecular dynamics with statistical mechanics, molecular simulation at different resolutions, machine learning, and experimental data. Our group works on the definition and implementation of strategies
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willingness to engage in interdisciplinary cooperation as well as cooperation with existing research groups in mathematical physics, dynamical systems, data science, machine learning, control theory
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, and therapy resistance mechanisms Ability to work independently and collaboratively within interdisciplinary teams Prior experience with network modeling or machine learning is a plus We offer