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Field
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-ray scattering, materials science, and/or experimental methods at large-scale research facilities Experience in scientific programming (e.g. Python), data analysis and handling/managing large datasets
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biochemical models, data assimilation, spatial analysis and GIS approaches. • Programing skills (e.g. R or Python) for data manipulation and visualisation, and to perform statistical analysis (e.g. mixed models
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programming, e.g., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed
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experimental fluid mechanics Enthusiasm, creativity, and a can-do attitude Programming skills (Ideally PALM-4U, Python / MATLAB or similar) Excellent communication skills in English (both spoken and written) You
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, and digital building technologies Experience with or motivation to learn programming and data analysis (e.g. Python, R) Personal suitability and motivation for the position Qualifications considered
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Experience particularly with 3D vision systems. Proficiency in the programming languages Python, C#, C and C++. Experience working with industrial robots (e.g., ABB, Universal Robots, Kuka, Yaskawa). Skills in
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., Python, MATLAB, etc.) The successful candidate must be enrolled in USN’s PhD program in Technology within three months of accession. For admission to the Programme, the weighted average grade of B
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
3D vision topics such as 3D mesh models, statistical shape modeling and articulated pose estimation Solid ML/AI foundation Strong programming skills in Python (CUDA is a plus) Hands-on experience with
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, computational biology, bioinformatics, data science, or related fields Strong interest in clinical and biomedical data, translational research, and health informatics Experience with programming skills in Python
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Strong background in differential equations and numerical methods Solid programming skills e.g. Python, C++, Julia or similar Interest in interdisciplinary research bridging mathematics and environmental