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Science degree (or equivalent, 240 ECTS) in Computer Science, Chemistry, Life Sciences, or a related field. Strong programming skills in Python Understanding of basic chemistry and biology concepts
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biology. The applicant should also have an interest in learning, or previous experience in, computer programming, particularly using languages such as Python. The ideal candidate is driven and a creative
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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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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