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, ASE) Python programming skills Preferably, experience with machine-learning interatomic potentials (e.g. MACE, NequIP, or similar) Preferably, knowledge of solid oxide cells, oxide materials
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master’s degree in computer science, mathematics, or a related subject. Experience with functional programming (e.g., Haskell) or proof assistants (e.g. Rocq, Agda, Lean). Good communication skills in
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candidate with experience in experimental research and a strong interest in cognitive neuroscience, brain development, and/or learning. Excellent analytical and programming skills, the ability to work both
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systems. Background in polymer science, soft materials, complex fluids, or related areas. Proficiency in scientific programming with Python and/or C++. Strong written and verbal communication skills
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in biology or related fields. Preferred Qualifications: A strong background in programming (e.g., Python or R or C++) is essential. Research experience utilizing skills of programming, statistics, and
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degree (MSc) in Civil Engineering, Remote Sensing, Geodesy and Geoinformatics, Aerospace Engineering, Data Science, or a related field. Solid programming skills in Python, MATLAB, C++, or other
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quantum mechanics, thermodynamics and statistical mechanichs Documented experience in programming Strong interest in atomistic modeling of surface reactions Good communication skills in written and spoken
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processing Some experience in SAR data processing or another field of array signal processing is an asset The successful candidate has strong analytical skills and programming experience in Matlab, Python
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Position B. A strong interest in fundamental research tackling questions on the perception of time and space in virtual immersive environments. Solid quantitative skills (R, Python, or Stata). Programming
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quantitative methods such as mathematics, statistics, and programming, broad knowledge of natural and anthropogenic processes affecting carbon storage, and a willingness to conduct fieldwork in remote and