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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer
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in computational fluid dynamics Experience in computer programming, in particular Python and Matlab, and in CAD and CAE tools Ability to work independently and also to enjoy collaborating with others
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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(Chapter 7, Section 39 in the Higher Education Ordinance (1993:100)). Desirable qualifications Master’s degree in mechanical engineering or equivalent subject. Good knowledge of computer-aided engineering
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Swedish, spoken and written good computer skills Meritorious for the position are: demonstrated competence in, or methodological orientation toward, qualitative research methods and theory development
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. Plant science/ecology, especially related to forest ecosystems. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Quantitative methods in
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, which provides a great opportunity to be involved in challenging development projects. Qualifications To be qualified for the position, you must hold a PhD degree in Control Engineering, Computer
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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Engineering, Computer Engineering, Mechatronics Engineering, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or other related subjects. Experience working on experimental
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming