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Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis. You will
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passion for teaching computers how to see, preferably have done some previous research in this field (e.g., internships, research papers, etc.), and want to make an impact in a societally relevant
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and Energy (HDS-LEE), the project offers an interdisciplinary research environment at the interface of bioengineering, computational biophysics, and data-driven modeling, with strong links to open
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the potential for long-term societal impact. Join us in uncovering the biology of aging and shaping the future of healthy longevity. Training and research within the PhD program is interdisciplinary. Lecture
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the HDS-LEE graduate school program. Supervise interns and student projects. Your Profile: Excellent Master’s degree in computer science, physics, or mathematics (or a related field), with a focus on
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research