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Field
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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of the (computational) mechanics of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux
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in working with large data sets and the development of numerical models. Basic knowledge of glaciology or geodesy. Good expertise in programming, e.g. in Python, MATLAB, or other high-level programming
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biochemistry are required Profound knowledge in bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications
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optimization. • Proficiency in programming (Python, R, Julia, or similar) and experience with frameworks like PyTorch, TensorFlow, or JAX. • Prior research in statistical learning and online optimization
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subject areas. Both working independently and working in a team, e.g. during the measurement campaigns, is particularly demanding. Knowledge of programming languages such as Python is an advantage
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themselves with new subject areas. Both working independently and working in a team, e.g. during the measurement campaigns, is particularly demanding. Knowledge of programming languages such as Python is an
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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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Information Systems (GIS), programming in Python, practical forestry, nature conservation, cultural heritage management, as well as a driver’s license, are considered assets. Place of work: Umeå Forms