36 machine-learning "https:" "https:" "https:" "UCL" "UCL" positions at University of Twente in Netherlands
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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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Vacancies Scientific programmer of libraries on testing and learning in Haskell and Python Key takeaways As a scientific programmer, you will support the development of software from a technical
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PhD position ‘Courage to Correct: Balancing Error Prevention and Learning in Strategic Crisis Teams’
Vacancies PhD position ‘Courage to Correct: Balancing Error Prevention and Learning in Strategic Crisis Teams’ Key takeaways In high-stakes crises, strategic teams often aim to avoid errors at all
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and application To learn more about the project, you may visit: https://www.utwente.nl/en/bms/pa/research/bridge/#project-team For inquiries, please contact Dr. Le Anh Long l.a.n.long@utwente.nl About
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policymakers; and (4) supporting the organization and implementation of a project conference. Information and application To learn more about the project, you may visit: https://www.utwente.nl/en/bms/pa/research
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Vacancies Postdoc position on Federated/Continual Learning for Time-Series IoT Data (TRUMAN Project) Key takeaways In this role, you will address the intricate challenge of enabling AI to learn
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. Screening is part of the selection procedure About the department The group of Prof. Guido Mul (<https://www.utwente.nl/en/tnw/pcs/>) is part of the Department of Chemical Engineering of the University
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at the University of Twente. https://www.utwente.nl/en/techmed/facilities/bioengineering-labs/biomaterials-biomembranes/ About the organisation The Faculty of Science & Technology (Technische Natuurwetenschappen, TNW
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motivation letter. For more info please visit our website [https://www.utwente.nl/en/tnw/mm/] or contact the secretariat of the Department Molecules and Materials secretariat-molmat-tnw@utwente.nl, or Prof. Dr
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to the development of innovative, physiology/ machine learning-driven clinical solutions and decision support tools for critically ill patients, focusing on cardiovascular and respiratory monitoring, mechanical