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educational system A scientific profile relevant for the nuclear medical applications research programme, as outlined above A solid background in scientific computing, including proficiency in Python
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programming (e.g., Python) Documented proficiency in deep learning frameworks (e.g., PyTorch) Documented background in machine learning, mathematics, linear algebra, and statistics Fluent oral and written
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frameworks. Programming languages such as e.g. Python, C++, and LABVIEW. In the assessment, the emphasis is on the applicant's potential to complete a research education based on the master's thesis
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analysis Solid programming experience (e.g. Python, R, MATLAB, GAMS or similar) Interest in environmental risk, emissions analysis, and sustainability transitions. Ability to work both independently and
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numerical analysis skills (e.g., Python, MATLAB) and/or experience with groundwater/geochemical modelling software (e.g., MODFLOW, PHREEQC). Experience with laboratory analytical methods (e.g., chromatography
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spectroscopy is highly beneficial Experience with and knowledge of mathematical modeling techniques (numerical solution of Partial Differential Equations) Programming and data analysis in Python Language
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Equations) Programming and data analysis in Python Language requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and
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. Desired qualifications: Strong theoretical and methodological capacities in statistics Documented expertise in computational methods and experience with R or Python programming Experience in Bayesian
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background in statistics (a minimum of 60 ECTS in statistics). Knowledge in programming skills (e.g., R, Python). Candidates without a master’s degree have until June 30, 2026 to complete the final exam
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background in fundamental or applied fluid mechanics. Previous peer-reviewed publications in well regarded journals. Programming skills in MATLAB, C, Python, or similar packages. Experience with state