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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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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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, Python, Julia, MATLAB). A research-oriented attitude. Ability to conduct high quality academic research, reflected in demonstratable outputs. Ability to be self-propelling and drive your own research
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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
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remote sensing/climate data. You have programming skills in Python and/or R; you are familiar with reproducible coding and automated geospatial data analysis. You have excellent scientific writing and
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. You have good programming skills in Python and/or R; you are familiar with reproducible coding and automated (geospatial) data analysis. You have excellent scientific writing and communication skills in
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in C++ or Python. Affinity with education and logistics. A proactive, independent working style. Eagerness to work on achieving societal impact. A Certificate of Good Conduct (VOG) will be required
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remote sensing/climate data. You have programming skills in Python and/or R; you are familiar with reproducible coding and automated geospatial data analysis. You have excellent scientific writing and