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. Experience with programming (for example Python/Matlab) and image analysis is highly recommended. Please share your GitHub code repository if you have one. In assessing the applications, special emphasis will
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programming and software skills (Python essential; C++/Fortran beneficial) Interest in machine-learning-based regression and surrogate modelling Motivation to challenge established CFD-driven design workflows
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Background in programming (Matlab, python, …), familiar with Multi-body dynamic tools and good knowledge
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chemistry, or Applied Mathematics or Information Technology. Experience with numerical programming, machine learning or data analysis, preferably with Python. Solid background in technical mathematics
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, the city and the arts Where to apply Website http://www.iuav.it Requirements Additional Information Eligibility criteria Evaluation of qualifications Interview Eligible destination country/ies for fellows
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, Computational Social Science, Natural Language Models, Physics, Mathematics, Computer Science, or related subjects. Proficiency in programming languages relevant to research (e.g., Python, SQL, Julia). Experience
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students; and 54 MS students) degrees. The McGowan Institute for Regenerative Medicine (https://mirm-pitt.net/ ), Computational and Systems Biology (https://www.csb.pitt.edu/ ), the Vascular Medicine
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data science. You must be curious and driven with excellent interpersonal skills and writing competencies. Experience with programming languages, notably Python or R, is expected. The work will imply
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, Python and/or R, and ability to manage and structure large datasets is essential. Interest/skills in application of AI methods to clinical data is an advantage. Stipend 2: Genetic Risk Communication and
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skills, Experience in programming in Python or another language, e.g., in C++, Matlab, R, Familiarity with basic concepts of dynamical systems, Knowledge of wind turbine dynamics is a plus, Curiosity to