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optimization • Experience of multidisciplinary work and collaboration between academia and external partners. • Good programming skills in Python (Pytorch) etc. • Additional knowledge on waste and Near-infrared
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of mathematical modeling and data analysis. Experience of programming languages and tools commonly used in biophysical or agricultural modeling (e.g., Python and R). Familiarity with food system resilience
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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of space and plasma physics Data analysis Programming skills (e.g., Python, Matlab, and/or C/C++) Proficiency in both written and spoken English. Terms of employment The employment is expected to result in a
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be considered if combined with advanced coursework in cell and molecular biology and genetics. Experience working in a Unix/Linux environment, as well as documented experience in R or Python, is
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tools for end-to-end processing of next-generation sequencing data, from raw data to variant discovery (e.g., GATK pipeline). Experience with programming languages (e.g. bash, Python, and R). Experience
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. Experience in implementing numerical methods and algorithms, e.g. in Python, Matlab or similar, is required. A strong motivation to develop mathematical tools for biological and medical applications is
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-ray crystallography, cryoEM) and/or analytical chemistry (e.g., mass spectrometry) Programming skills (e.g., in R or python) Ability to work independently, take initiative, and collaborate within
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. The applicant should have strong background in mathematical foundations of computer science and experience in Python programming. Previous experience in deep learning, reinforcement learning, or explainable AI is