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independent work and effective collaboration, particularly during measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Participation
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, particularly during measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Practical laboratory skills and an enthusiasm
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programming languages such as Python and experience with deep learning frameworks (e.g., PyTorch, TensorFlow) is highly desirable strong interest in interdisciplinary research combining imaging, machine
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study to be used as parameters in the model. 4) Model Implementation: Implement the model in Python, perform testing, and validate its performance based on the collected data. Applications must be
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experience in pytorch and/or tensorflow) knowledge of statistical methods and programming (R and Python) prior experience in machine learning and ideally also on applications in the health domain and/or
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or equivalent) in physics A background in solid state physics is highly recommended Aptitudes in programming (Python) are a plus Proficiency in English (working language at the ESRF) Working conditions Your shall
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performance, detect artefacts, and ensure scientific rigor Proficiency in Python (or Julia/R) for data handling, ML model development, and statistical analysis Ready to work with time‑series data, sensor fusion
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highly motivated candidate with: Master’s degree in medicine (MD) Strong interest in translational endocrinology and digital health technologies Basic programming or data science skills (R, Python) and
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programming skills (Python, MATLAB), excellent communication and ability to integrate numerical modelling, sensor technologies, and occupant-focused design. Experience in thermodynamics, building physics
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teaching assistantship. The ideal candidate will have a strong foundation in Python programming and hands-on experience with deep learning frameworks such as TensorFlow or PyTorch. Applicants with a