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scientific ideas. Previous experience with statistical analysis, programming (e.g., R or Python), machine learning, or genomic data analysis is an advantage but is not required. We welcome applicants who
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involve scientific programming, analysis and documentation of results, and dissemination through peer-reviewed publications and international conferences. The position is offered within the Center for
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machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph representation learning. Programming skills (e.g., Python) and experience with deep learning
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algorithms. Proven experience with reinforcement learning algorithms and implementations. Experience in programming, e.g., in Python, PyTorch, TensorFlow, or similar. Curiosity and willingness to
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, data analysis and programming skills (e.g., R, python, matlab, etc). We seek candidates that are team players who can play active scientific and social roles in a diverse and international lab setting
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statistical programming, preferably in R Strong analytical and problem-solving skills Excellent collaboration and communication skills Excellent written and spoken English proficiency The ability to work
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advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch or TensorFlow, and be motivated to combine
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engineering, robotics engineering, or a related field. Programming skills in Phyton, C++ and/or C# are advantage. Willingness to design, plan and conduct experiments in able bodied participants. Fluent in
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. The position will require the candidate to work both on the front and back-end of the system utilizing full technological stacks. The ideal candidate must have excellent programming skills and
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acquisition, equipment construction, machine learning, and image analysis. You master programming in for example Python, MATLAB, or a similar platform and you are motivated to further develop your