422 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" positions in Denmark
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participants and schools, coordinating data collection and managing ethics procedures Conducting school visits to engage directly with children, observe their behaviour and preferences, and collaborate with
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publications in leading international venues. - Guiding and working with Master and Ph.D. students at ECE and collaborators as needed. More information - see the attached link or email: sshreya AT ece.au.dk
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. Interdisciplinary collaboration is central to our culture. BCE maintains strong partnerships across Aarhus University, including with the Departments of Mechanical Engineering, Electrical and Computer Engineering
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Job Description The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark
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. Interdisciplinary collaboration is central to our culture. BCE maintains strong partnerships across Aarhus University, including with the Departments of Mechanical Engineering, Electrical and Computer Engineering
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of BRIGTH and ensures effective development and implementation of strain design procedures in our design-build-test-learn workflow using big data and data science. The Analytics team is part of
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robotic system capable of autonomously performing standard echocardiography. Your primary tasks will include: Setup annotation platform for labelling Echocardiography videos. Supporting data collection and
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international partners for research projects Regular administrative tasks such as data entry, data gathering, and testing interfaces. Assistant with planning and working events hosted by the department Who we
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well as interviews with the students and their families. Further information Applicants are encouraged to contact project manager Laura Gilliam (lagi@edu.au.dk ) to obtain the full project description. The position
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals