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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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theory and hands-on; Proficiency in programming in Python and deep learning frameworks such as PyTorch and TensorFlow; Excellent communication skills in oral and written English; Creativity, thoroughness
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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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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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dynamics of fluid and thermal systems. Proficiency in programming and data analysis tools, such as Python and MATLAB (or equivalent). Excellent proficiency in English, both spoken and written. Assessment
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Optimal Control Theory Strong programming skills in C++/Python/MATLAB Experience with algorithms for dynamics and control of high DOF multi-body systems (such as robots) Excellent communication and writing
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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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technology, also documented experience of technical programming in e.g. Python or Java are a merit. Experience with modelling and simulation in stormwater management are an added advantage. assessed ability
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at least 60 credits must be at the advanced level A completed degree project in computational science related to physics or another subject relevant to the project Experience in programming with Python
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experience. Certified training in R and Python software. Documented experience using machine learning and large, multimodal human datasets. Emphasis is placed on the candidate’s personal qualities, including