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Python or C/C++. The candidate should have an interest in developing novel bivariate methods in machine learning for molecular property prediction within an interdisciplinary application. Ideally
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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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simulation models Programming skills (e.g. Matlab or Python) Willingness to supervise young scientists Enthusiasm and enjoyment of working independently on developing fresh ideas and solutions Good
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good programming skills (Python or C++) good English skills (spoken and written) interest and enthusiasm for scientific issues good communication skills independent, autonomous and committed way
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skills. Experience with 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
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skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX or PyTorch, is a plus. In addition to above-average interest in the topic
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beneficial Experience in working with mouse models Advanced programming skills in Python are beneficial Strong motivation and ability to work both independently and collaboratively as a member of
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Programming skills (e.g., Python, R, C/C++) Knowledge of workflow management systems (e.g., Snakemake) is beneficial High motivation for scientific work and willingness to contribute to an interdisciplinary
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systems. Experience with robotic hardware (e.g., robot arms) and proficiency in C++ and/or Python, ROS 2, and MATLAB. Solid background in control theory and/or machine learning is highly desirable
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and/or analysing data (e.g. Bash, R, Python) We offer Excellent development opportunities, extensive training and an attractive remuneration package An exciting interdisciplinary and international