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simulation and machine learning funded by the Klaus Tschira Foundation. Profile Solid grounding in statistical mechanics Experience with machine learning and/or molecular simulation; strong Python and PyTorch
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multidisciplinary team Basic knowledge of detector systems for particle physics Basic programming skills, e.g., python, Matlab or similar languages Fluent spoken and written English Proficiency of the German language
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of numerical methods Basic programming skills, e.g., Python, Mathematica or similar languages Fluent spoken and written English Proficiency of the German language is a plus. We offer: a unique opportunity to
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
training program that promotes cross-disciplinary collaboration and provides in-depth scientific insight as well as a systematic approach to marine data science. For more information, visit: https
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characterization techniques such as XRD, XPS, SEM, or TEM. Experience in data analysis, scientific programming (e.g. Python), statistical experimental design, as well as data-driven research methods and
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of the Max Planck Institute for Human Development (Berlin). The candidate will lead arc 1 and 2 of ATLAS (see https://www.mpib-berlin.mpg.de/research/research-centers/lip/projects/atlas ) in all steps
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be advantageous: Experience with scientific expeditions Experience in computer-aided analysis of biological sequence datasets (e.g., with R, Python and Bash/Linux environments) Basic understanding
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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at least one programming language (e.g. Python, C++) ▪ FPGA programming experience ▪ Interest in hands‑on experimentation and hardware prototyping The following points are considered a bonus ▪ Experience
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FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch