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Extensive knowledge of X-ray methods Knowledge of synchrotron science Knowledge of catalysis Experience in energy storage Experience with programming languages (ideally Python) Fluent in written and spoken
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Biology, Computer Science or related studies) Experience in Python with PyTorch (or equivalent) programming Experience in sequencing data analysis Basic knowledge in machine learning Experience with linux
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natural sciences expertise in materials science and materials engineering, in particular methods of computational material science (e.g. DFT, CALPHAD) programming skills, e.g. Python basic knowledge of data
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Python in an existing modeling framework. This will include generating a better understanding of the production process and its constraints and techno-economic parameters. The master`s thesis involves
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solid working knowledge of Linux environments and scripting languages (e.g., Bash, Python) strong teamwork, combined with a structured, independent, and detail-oriented working style good command
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science, cognitive science, applied mathematics, physics, neuroscience or a related field A good command of Python for data processing (MNE python, NumPy, Pandas) Hands-on-knowledge in signal processing Experiences
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information. Knowledge of the functioning of quantum hardware (in particular of neutral atom quantum computers) is highly desirable Proven experience in Python and in programming quantum computers e.g. with
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. The algorithm is then tested for effectiveness and efficiency against an existing data set. What you will do You will design and realise the concept in Python You carry out a literature research, design
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/or genomics is required Strong analytical skills as well as broad experience with scripting languages (e.g. Python, R, Bash); knowledge of common bioinformatics software and access to databases
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are expected. Knowledge in parallel programming is desirable. Prior knowledge in differential-algebraic equations, Gaussian processes or kernel based methods is a plus; programming experience in Python or C/C