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of the following areas: Image processing, partialdifferential equations, scientific computing, deep learning.•Solid programing skills. Knowledge of Python, Tensorflow/Pytorch, and Mathematica.•Fluent
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developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
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applications of AI. Proficiency in Python, leading ML frameworks (e.g., PyTorch, TensorFlow, JAX), and scientific libraries (e.g., NumPy, SciPy, scikit-learn) Familiarity with medical images such as x-ray, CT
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applying and developing deep learning models (e.g. CNNs, ViTs, or geometric deep learning) Proficiency in Python and PyTorch Motivation to work with interdisciplinary clinical partners A track record of
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programming skills in python and preferably a compiled language such as Java or C++. Clear evidence of deep learning proficiency, reflected through coursework and GitHub repositories. Postdoctoral candidates
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Stata, R and/or Python. a scientific mindset, inquisitive personality, team player, and the capacity to work independently; In our international working environment, there is an increasing amount
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field. Proficiency in deep learning and exceptional programming skills in python and preferably a compiled language such as Java or C++. Clear evidence of deep learning proficiency, reflected through
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process engineering, environmental sciences, or another related field You have expertise in one or more of these areas: Data management and programming (e.g., Python) Life Cycle Assessment (LCA) Multiple
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process engineering, environmental sciences, or another related field You have expertise in one or more of these areas: Data management and programming (e.g., Python) Life Cycle Assessment (LCA) Multiple
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, such as R, Python, or Machine Learning, to identify patterns in biological factors, disease and mortality; co-supervising and mentoring PhD candidates, MSc and BSc students; collaborating with national and