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. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
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experience and enhanced potential to receive an ERC Starting Grant in the future. Open to both PhD (natural sciences) and MD (medical sciences) holders. From a variety of academic backgrounds: molecular
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of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
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to serve as the basis of published manuscripts Write manuscripts describing research results. Write grants and progress reports related to research funding. Qualifications PhD or MD required Strong
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning
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Engineering. Therefore, the department invites applications from candidates who are driven by excellence in research and teaching as well as external collaboration on societal challenges. The position will be
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are not limited to: Machine Intelligence, AI for Science, Scientific Computing, Robotics, Complex Systems Modeling, Control, and Decision Making, Autonomous Agent and Multi-Agent Learning, Computational
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platforms involving sensors, instrumentation, and physical measurements Involvement in the design, wiring, commissioning, and troubleshooting of systems Collaborate closely with PhD students, postdocs, and
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, and develop CNS drug discovery and development programs. Our expertise spans sensory neuroscience, substance use disorders, learning and memory, neural control of metabolism, neurodegeneration, and