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bioinformatics such as Python, R, EdgeR, Cytoscape, ggtree, etc., as well as courses in data visualization and web development will be considered. At least 2 publications as first author and more than half a dozen
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Python, PyTorch or TensorFlow) and practical experience with generative models (e.g. LLM, diffusion models, GAN); Ability to conduct independent research and work in a team, including a willingness to
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background in, or willingness to learn, physics-based numerical modelling and programming skills, in Python (preferably), R, MATLAB, or a comparable language. Openness to collaborate within interdisciplinary
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experience with: Reinforcement learning. Neuro-musculoskeletal modeling Knowledge of the following is a plus: Real-time programming (C++, Python) Real-time communication systems (e.g., EtherCAT, CAN Bus
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-motivation and interest to learn new skills Great to have: Experience programming in Python, Julia, or C/C++ Experience with Mathematica Experience with finite element methods, agent-based simulations, and/or
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, Engineering, Mathematics, Psychology, Linguistics, and/or other relevant areas Previous experience in participating in research projects (e.g., data collection, analysis). Strong programming skills (Python
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programming skills (e.g., Python and/or Matlab) are expected. Your workplace and main supervisor will be at the Swiss Federal Research Institute WSL in Birmensdorf (approx. 20 min outside of Zurich
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
(Python, Supervised learning, Multi-objective optimization) Additive manufacturing of metals Corrosion characterization Mechanical testing Great emphasis is put on personal qualities such as the ability
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 12 days ago
limited to Python, OpenCV, PyTorch, Unreal Engine and C++ Good oral and written communication skills in English A natural team player and detailed-oriented person Some academic background or general
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science, or a related field. Strong background in quantitative methods and statistical analysis. Experience with computational tools for large-scale data analysis (e.g., Python, R, SQL). Familiarity with