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Field
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experience in NGS data analysis. relevant experience in statistical data analysis and programming (e.g. R, Python, Perl, C++) as well as with workflow management systems (e.g. snakemake, CWL, Nextflow
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in Python with knowledge of NumPy, Pandas, SQL, Bash, Docker, git, etc. Willingness to clean large, messy datasets Excitement about clean, structured code Conscientiousness in implementing, testing
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, chemical engineering, or a related field Experience in modeling (e.g. using Aspen, AVEVA, Python) is an advantage but not required Knowledge of thermodynamics, process engineering, and electrochemistry is a
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academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and
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mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and experience with the Linux operating system
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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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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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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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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