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University of Warsaw: Faculty of Mathematics, Informatics and Mechanics | Poland | about 1 month ago
comes with no teaching obligations BASIC RESPONSIBILITIES AND OBLIGATIONS Conducting research related to the scientific project titled “Calculus of variations in machine learning problems”, in particular
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well as building competence to relate professionally to religious and worldview diversity for individuals in public service such as administration, health care, correctional facilities or the armed forces
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of manuscripts, presentations, conferences, and grants. Preferred Qualifications Equipment Utilized Physical Demands and Work Environment Overview Candidates must be highly motivated, open to learning new
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, Computer Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential machine learning applications. Position Objective
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care, our work is aimed at creating spaces for collaboration, critical analysis, reflection, and learning. About the organisation At the Faculty of Behavioural, Management and Social Sciences (BMS), we
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, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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of Science at UvA. What are you going to do? The aim of the project is to use advanced Machine Learning techniques to predict the anharmonic vibrational spectra of large Polycyclic Aromatic Hydrocarbon (PAH