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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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engage with clinical, industrial, and academic partners Experience and strong research interest in one or several of the group’s research focus areas Programming skills in Python/MATLAB, C/C++ and
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well as energy-economic analyses. Prior experience with software packages such as GAMS, Python Pyomo, and solvers like Gurobi, CPLEX, etc. Excellent German and English skills (spoken and written). Admission
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preferably with data analysis and machine learning (e.g., Python, AI frameworks). You have strong analytical and problem-solving skills, with the ability to translate complex clinical processes into structured
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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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expect to obtain your Master’s degree with the above-mentioned experience around the starting date of the appointment. You have experience in computing languages such as R, Python or similar. You bring
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or habitats knowledge of data analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity
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well as data analysis and interpretation. Previous experience in fieldwork, laboratory techniques (chemical analyses), and advanced data analysis will be highly valued. Programming skills in R or Python
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analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity research Great emphasis
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expect to obtain your Master’s degree with the above-mentioned experience around the starting date of the appointment. You have experience in computing languages such as R, Python or similar. You bring