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Field
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ideally includes past or present projects centered on machine learning analysis of chemical or biochemical data, especially relating to structural biology. Ample experience with Python programming is
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constitutive models in Matlab or Python. Position 2 – Ply/ply and tool/ply friction during hot press forming Excessive friction between the plies in a laminate or between the outer plies and the tool surfaces
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or soon to be finished Background in protein design, computational biology or related field Working knowledge in at least one relevant coding language (Python, R, or C++) Excellent communication skills and
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studied Specific Requirements Familiarity with statistical programming languages (e.g., R and/or Python) will be valued. Familiarity with statistical programming languages (e.g., R / RStudio and/or Python
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for graphs; 4. Practical experience in the analysis of scientific data; 5. Proficiency in programming with Python; 6. Familiarity with the drug discovery process; 7. Ability to work on interdisciplinary
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Desirable: Experience with NMR spectroscopy and/or single-molecule fluorescence techniques Programming/data analysis skills (e.g., Python, MATLAB) Previous research experience in structural biology or protein
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rheology and can implement constitutive models in Matlab or Python. Position 2 – Ply/ply and tool/ply friction during hot press forming Excessive friction between the plies in a laminate or between the outer
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programming experience with Python are beneficial but not required. We particularly encourage women and candidates from other groups which are currently under-represented in academic posts. The preferred
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, or a related discipline Interested in climatology/meteorology as well as quantitative methods Prior experience in programming is a plus (e.g., using R or Python) Good communication skills and a high
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PhD position understanding and designing nanomedicines-membranes interaction: physics based approach
analysis and programming experience with Python are beneficial but not required. We particularly encourage women and candidates from other groups which are currently under-represented in academic posts