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of X-ray methods Knowledge of X-ray optics Knowledge of synchrotron science Knowledge of catalysis and energy storage Experience with programming languages (ideally Python), SPS controls system Fluent in
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degree in computer science, mechatronics, or electrical engineering. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage). Knowledge of computer
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, catalysis studies - in particular electrocatalysis and Python programming Experience within the following fields is highly beneficial: Transmission electron microscopy, Electrochemistry, Image analysis, Big
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and interest in working with custom-built or modified instruments Solid programming skills (e.g. Python) are desirable Ability to work independently and self-reliantly, while maintaining strong teamwork
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, materials science and/or process engineering systems is an advantage Knowledge of relevant programming languages for data processing/evaluation, especially Python/ Matplotlib, is an advantage Independent
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of the (computational) mechanics of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux
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Proficiency in at least one programming language (Python, C++, …) Keen interest in neuroscience is essential Experience with modelling, analysis of complex dynamical systems, simulation, analysis of large-scale
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in the field of energy storage Experience with programming languages (ideally Python) Fluent in written and spoken English Very independent and self-motivated way of working but also excellent teamwork
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processes. We also welcome applicants with an MSc degree in Biology or Biochemistry who possess a solid aptitude in the use of the command line and knowledge of a programming language (i.e. python
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 37 minutes ago
programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above-average interest in