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. Your experience and ambitions The position requires excellent programming skills in Python with demonstrable familiarity with PyTorch, experience in working on shared codebases, excellent applied math
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mathematics, computer science, or a related field, and strong programming skills, to work on biology-informed machine learning for dynamical systems (see project description below). The position is based at
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sciences, geoinformatics, physics, computer science, or a related field. Strong programming skills, for example in Python or R, are required. Experience with point cloud processing, terrestrial or airborne
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simulations Magnetism in polycrystalline microstructures Magneto-mechanical interaction in ferromagnetism Experience or strong interest in the following areas is highly desirable: Programming skills
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learning, particularly physics-informed or physics-constrained learning Programming and modelling skills (Matlab/Simulink, Python, C or other embedded-systems languages) Interest in embedded systems and
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measured data (an interest or aptitude here is enough; we don’t expect prior demonstrated experience) Good programming skills – you are required to provide a sample of your code during the
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writing skills; solid programming and mathematical skills (Python/C++, ROS valued); fluent English. Position-specific plus: mobile robot perception, SLAM, motion prediction, and field-robotics
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, computer science or other related fields) Good programming skills in R and/or Python ; experience with Unix/Linux environments and bash is considered an advantage Prior experience in the preprocessing
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doctoral researcher(PhD student) with a strong background in probabilistic machine learning, statistics, applied mathematics, computer science, or a related field, and strong programming skills, to
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strong interest in the following areas is highly desirable: Programming skills (MATLAB, Python, or C/C++) Real-time and instrumentation platform (dSpace, LabView) Microscopic measurements (X-Ray, EBSD