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Field
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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interest in historical research, migration, and digital infrastructures Familiarity with digital tools and languages such as Wikibase, SPARQL, RDF, Python, GitHub, and Jupyter Notebooks is highly desirable
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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into account as disruptive events, and which strategies can be derived from this for a resilient system design. Your contribution to scientific analysis: Further develop existing energy system models in Python
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degree (2.1 +/MSc) in mechanical / civil / environmental engineering, physics or a related quantitative field; strong computing skills (Python/MATLAB/GIS); interest in transport or urban futures. Position
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forms from land via inland waters to sea. You will synthesise, test, and use the reported methane kinetics from labs and culture experiments to construct the model using Python programming language. You
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publication record #excellent programming skills in Python or at least one other scientific programming language (e.g. FORTRAN, C, Matlab, R) #good knowledge of English (written and oral) #high degree
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experience with programming tools such as R or Python. An interest in acquiring new data science and programming skills is required. A keen interest in teaching and academic development. An excellent academic
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Python or at least one other scientific programming language (e.g. FORTRAN, C, Matlab, R) good knowledge of English (written and oral) high degree of creativity and flexibility; ability to work under
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skills : We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and