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Aerospace Engineering, Aeronautics or a comparable degree, thorough knowledge of AI/ML methods, acoustics, and air traffic management are preferred, as well as excellent programming (Python, Java, C++, …) and
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Bench Strategy File); managing the progress of the action plan with the different stakeholders (Test Bench Operators, New Space primes, ESA interfaces) in a project mode (schedule, risks, costs, reporting
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and verification techniques for the design of the Drag-Free Attitude and Orbit Control System of the Next Generation Gravity Mission. To achieve this goal, four different objectives must be fulfilled
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Sciences) or Data Science (Bioinformatics, Computer Science, Data Science, Artificial Intelligence, Computational Biology) Experience with different programming languages / environments such as, R, Python
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programming and software development. Familiarity with Python and statistical computing libraries, like PyTorch or JAX, etc., would be preferred. You are a motivational teacher, with an encouraging teaching
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. Building on these insights, you will run one dimensional mixed layer models to test how different conditions regulate stratification and mixing, and compare modeled responses with observations to expose
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specialization in Data Science (Bioinformatics, Computer Science, Data Science, Artificial Intelligence, Computational Biology) or Life Sciences with strong affinity to Data Science. Experience with different
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PhD Candidate on The Future of Mixed Methods Research /Junior Lecturer in Methodology and Statistics
are appreciated but not required. Good research skills evidenced by good grades for research methods courses. Excellent data analytical skills, as evidenced by a good command of R and/or Python Experience with
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diverse group of people from different countries and disciplines, and we welcome candidates who contribute to and enjoy this diversity. Job requirements You must be able to demonstrate: Masters degree in
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environmental datasets; proficiency with Python, MATLAB, or similar scientific programming environments. Ability to work with large datasets, develop reproducible workflows, and apply modern data science tools