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contribute 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
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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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to 20 months. The salary scale is 10.0. Additional comments 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
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. Additional comments 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 Website
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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Electrical Engineering, Computer Science, or a related discipline. A research-oriented attitude. Solid background in machine learning and optimization methods. Knowledge and experience in (wireless
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methods for evaluating intelligence in people are not suitable for AI and vice versa due to inherent differences in learning, memory, and processing between these systems. This project develops
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You hold a PhD in Computer Science, Artificial Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and