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, multiphase flows, or similar areas. A deep understanding of the physics and dynamics of fluid and thermal systems. Proficiency in programming and data analysis tools, such as Python and MATLAB (or equivalent
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related field, Knowledge in fluid mechanics and heat transfer, Programming skills (Python, MATLAB or equivalent), Strong English communication skills. Experience in multiphase flows, modeling, or AI methods
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of medical imaging technology and physics. Specific proficiency in relevant software and programming languages, e.g. Matlab and Python. Basis for assessment and selection In accordance with the provisions
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. Strong programming skills in R and/or Python are essential, as well as prior experience in data analysis, statistics, or machine learning. The project involves large-scale single-cell and spatial
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, multiphase flows, or similar areas. A deep understanding of the physics and dynamics of fluid and thermal systems. Proficiency in programming and data analysis tools, such as Python and MATLAB (or equivalent
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at the master’s level, strong programming skills in Python, and experience with at least one of the popular deep learning libraries (PyTorch, TensorFlow, Keras, etc.). Good verbal and written communication skills
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on the following assessment criteria: Knowledge in energy technology, large language models (LLMs), deep learning, and Python programming. Meritorious qualifications include knowledge in power engineering, power
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programming skills in Python are necessary, along with an interest in combining physics with modern computational tools. Good knowledge SQLite is beneficial. Excellent ability to communicate in English, both
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modeling reaction kinetics. Proficiency in Python programming. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB
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desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS and R is a merit. Proven excellence in written and spoken English is essential. The fieldwork will