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Field
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are looking for an enthusiastic individual with a degree in a quantitative discipline. Experience of geospatial analysis (with GIS) is essential and programming with code (e.g. R, Python) would be advantageous
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. This research is ideally suited to candidates with interests in photonics, metamaterials, ultrafast optics, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental
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Python, Julia or C++ Knowledge of modern deep learning frameworks (e.g. pyTorch) Knowledge of collaborative software development tools (e.g. Version control: Git) Experience working in Linux shell/cluster
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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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in mechanical engineering, electrical engineering, computer science, AI, or related field, with outstanding study results. DESIRABLE REQUIREMENTS: Programming experience in Python, particular
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 2 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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: Working knowledge of MATLAB/Python and signals processing Understanding of electromagnetics Experience with CAD and mechanical design How to apply: Interested candidates should submit a full formal
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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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the application of machine learning and artificial intelligence. By using neural networks developed in Python, the project aims to generate robust and generalisable models for scaffold design. Industrial