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and MA teaching is conducted in Danish, but applicants must also be able to teach and supervise in English at university level. Applicants who are not fluent in Danish will be expected to acquire
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Job Description You will join a supportive and dynamic research team working at the intersection of machine learning and operations research. Your main task will be to design and implement ML
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externalities of transport. The division is interdisciplinary with scholars originating from transportation engineering, economics, psychology, computer science, social data science, machine learning, mathematics
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some background in one or more of the following areas: Mathematical Optimization / Operations Research Reinforcement Learning, Machine Learning, and/or Multi-agent systems Game Theory Algorithms
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processing, or spectroscopy. Familiarity with hyperspectral imaging or related optical imaging methods is an advantage. Strong programming skills in Python and/or MATLAB. Interest in applying machine learning
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and
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the interplay between qualitative and quantitative methods and data. There is a growing focus on novel computational methods such as NLP, machine learning, and AI within the group. Teaching activities in
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processing and hybrid BCI design Machine learning (ML) Bioinspired control systems Neuroplasticity and motor recovery Real-time control of soft exoskeletons Your Role As a PhD candidate, you will: Develop and
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stronginterest and experience with GIS data and tools for urban mobility with someprogrammingskills of Python/R, JavaScript, database management environments, Geographical AI and machine learning workflows
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include: Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and mountain glaciers), with proficiency in MATLAB/Python/Fortran, and related software tools