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in Python and working with machine-learning frameworks and libraries, e.g., PyTorch, TensorFlow, Hugging Face Strong conceptual understanding of clinical and biomedical research, data standards, and
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, or academic projects • Experience in writing research code in collaborative settings using languages such as R and Python • Ability to work effectively as part of a multi-disciplinary research team • Strong
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representations and their alignment with humans Development of Python code Collaboration on publicly funded projects Publication of research papers and patents Travel to international conferences, participation in
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. Documented research experience in modern deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning
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in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow, PyTorch) Experience with physics-based modeling Strong analytical and problem-solving skills, with
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, or a closely related quantitative field, together with strong programming skills, for example in Python or R. You are welcome to apply should you have a degree in applied parts of statistics
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architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch, including training and evaluating models on GPU/HPC infrastructure; • experience working with
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, or a closely related area is required. Experience: Demonstrated experience in strong optimization computational skills, proficiency in one of the programming languages R, Python, Matlab, and C++, and
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using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required
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relevant research areas Proficiency in Python programming Excellent written and verbal communication skills in English Writing scientific papers and exploring new technologies. Application and Selection