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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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to have experience in one or more of the following areas: Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization) Additive manufacturing of metals Corrosion
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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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rotor blades? Great! Perhaps you have already carried out modal analysis and have experience in working scientifically. Are you familiar with programming languages such as Python and eager to pursue a
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rotor blades? Great! Perhaps you have already carried out modal analysis and have experience in working scientifically. Are you familiar with programming languages such as Python and eager to pursue a
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code via differential testing)We focus on techniques that apply to real-world software systems. E.g., in the past, we have developed techniques that find and fix bugs in widely used Python, Java, C/C
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Physics, Time-Resolved Optical Spectroscopy, Photochemistry, Functional Material Dynamics, Laser Physics or Ultrafast Optics Experience in Python, MatLab or C++ is an advantage Good communication skills in
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scientific questions Proficient in scientific software (e.g., Gatan DigitalMicrograph, Python, Origin, Matlab, SRIM/TRIM) Basic knowledge of scientific data analysis and statistical evaluation Good command
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analytical chemistry, mass spectrometry, or trace gas measurements is an asset Enthusiasm for laboratory and field work Willingness to engage in programming and data analysis (preferably Python) Excellent
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focus on physical and mathematical aspects is required. In addition, scientific programming skills (preferably in Python) and experience with numerical models are essential. Desirable qualifications