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Post doc position in theory of machine learning at Department of Computer Science, Aarhus University
A post doc position in theory of machine learning is available. The post doc is under the supervision of Professor Kasper Green Larsen, Aarhus University, Denmark. The focus of the research project
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. This position is funded by the Danish Research Council Project 1 (DRC-1), which aims to address fundamental problems in geometric singular perturbation theory within the setting of slow-fast analytic vector
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for the successful applicant. The daily working language is English. Our research teams work in several fields, and we therefore expect you to have a background and qualifications in some of the following areas
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investigator (PI), Associate Professor Dan Bang, for examples of research topics. About the position The successful applicant will support the lab’s research activities. This includes data collection during DBS
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with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is part of DTU’s Tenure Track program. Read more about the program and
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part of DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU here . Further information Further information may be
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position. The position is part of DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU here . Further information Further
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activities will be carried out within both DTU Sustain and DTU Food departments. In QSA, you will become part of a dynamic and team-based research environment with around 50 international staff members
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in the areas of aquatic biology and ecology, Arctic environment and ecosystems, biodiversity, conservation biology and wildlife management. The Department currently employs approximately 275 academic
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in the areas of aquatic biology and ecology, Arctic environment and ecosystems, biodiversity, conservation biology and wildlife management. The Department currently employs approximately 275 academic