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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
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Machine Learning. We are looking for a motivated candidate, who has interest in both theoretical, methodological and applied research in anomaly detection in sequential data settings, and who is excited
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equations (PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in this role
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of current work processes. The project will adopt social science and sociotechnical perspectives such as computer supported collaborative work, HCI or organizational sociology to investigate the intra- and
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optimization. Experience with quality-diversity methods is a plus. • Experience with machine learning and artificial intelligence. • Strong programming skills (e.g., Python, C++), and familiarity with ROS
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acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment is to be made in accordance with NTNUs
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well as interest and knowledge of the broader field. The department has both analogue and digital workshops, and our new associate Professor must be able to supervise and teach across all technical processes
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well as to develop new courses in areas such as statistics, data science, machine learning and risk analysis. The department has long-term teaching obligations in NHH’s bachelor program in economics and business
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of Oslo for the project: DC14 - ESKAPE pathogen adhesion to cells and implant surfaces Supervisors Dirk Linke: https://www.mn.uio.no/ibv/english/people/aca/dirkl/index.html Håvard Haugen: https
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integrated into creative and artistic subjects to enhance human creativity, learning, and formation. The position allows for research into various ethical considerations related to the use of AI in the arts