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analysis, Python programming, and deep learning frameworks (e.g., TensorFlow, PyTorch) is expected. Prior work in cancer research or medical imaging is an asset. The successful candidate will join an
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multidisciplinary team environment. Further, we will prefer candidates with some of the following qualifications: Solid background in programming using Python (PyTorch, TensorFlow), R or other languages. Experience
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excellent skills in modern computer programming languages such as C++, Python, MATLAB or R. We look for candidates who enjoy collaborating in interdisciplinary teams and are good at communicating science in
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); Experience of statistical or other programming languages to manipulate large-scale datasets – e.g. Python, R; Strong quantitative skills and analytical reasoning applied to observational data; A track record
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of the following qualifications: Extensive experience in programming using Python, R, or other languages Research experience in greenhouse gases, or ecological experiments Insight into global
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structure- and ligand-based drug design methods (e.g., docking, QSAR, classic molecular dynamics, etc.) Familiar with all aspects of protein-ligand interactions. Solid python programming knowledge and good