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, computer science or mathematics (or a related field), with a focus on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good
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part and engage in 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
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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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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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, 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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of results through high-quality publications and open-source software contributions Your Profile: Master’s degree in chemical engineering, biotechnology, computational biophysics, bioinformatics, data science
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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language
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-of-the-art machine learning and computer vision methods and their applications Your Profile: Excellent Master’s degree in engineering, computer science or mathematics (or a related field), with a focus
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at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and computer vision for the life sciences Your Profile: Excellent Master’s degree in engineering
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, computer science and earth science/engineering, or a related field Proficiency in at least one programming language (Python, Matlab, R, C++, Julia, …) Good analytical skills with a sound understanding of data