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students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading
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development) including robotics, computer vision, natural language processing, information organization and retrieval, biomedical application and machine learning. Author of at least 2 research papers in topics
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Education and Experience: Appropriate PhD in a related field. Preferred Qualifications: Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in
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functional theory) and high-performance computing. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to
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description and duties The postdoc fellow will conduct research at the borderline between the fields of information visualization / visual analytics as well as machine learning in close collaboration with
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development in large multi-site cohorts; and 3) developing advanced machine learning models of task-related brain function. The fellow will have the opportunity to contribute to these projects and will also be
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assembly and annotation Experience working on computer clusters and handling large datasets Laboratory skills including DNA/RNA extraction and library preparation Demonstrated advanced bioinformatics skills
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primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or
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Associate to undertake fundamental and applied research into novel deep learning approaches to analysing LiDAR and vision data in forest imaging and remote sensing. The role is part of a three-year project
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of computer vision. Furthermore, the Center for Biosystems and Biotech Data Science, which has a headcount of four professors and ten PhD students, is responsible for organizing nine courses at GUGC (for 65