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the ability to train and manage student researchers and technicians. Preferred Qualifications Preferred experience: in vivo imaging, ex vivo electrophysiology, rodent behavior, Python/R/Matlab coding
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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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., Python, C++, or embedded systems). Strong interpersonal and intercultural skills, with the ability to engage rural communities. Willingness and ability to travel frequently for extended fieldwork in Kenya
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analysis, and/or machine learning (e.g., Python, Scikit-learn, PyTorch, etc.) is also desired. A track record of publishing in peer-reviewed journals on related topics is also strongly preferred. Application
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or disease modeling in R and/or Python statistics data analysis communication (written and verbal) This does not mean you need expertise in these areas but rather that you have some base knowledge upon which
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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, or similar. Good knowledge in programming (e.g. C or python) Experience in 3D image segmentation. Track record of producing high-quality research Documented pedagogical skills and pedagogical training
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experiments Documented expertise in data analysis using scripting (ideally python-based) Experience carrying out SAXS/WAXS experiments at large scale facilities Working experience with soft matter and/or
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-based imaging techniques (TEM, fluorescence, histology etc.) Successful grant applications Experience in Python programming Having worked on diverse science projects, in international surroundings
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and