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University Medical Center Utrecht (UMC Utrecht); yesterday published | Netherlands | about 2 months ago
fundamental methods research to guide in these analytical challenges. In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant
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We are seeking a highly motivated PhD candidate to join our research team in the field of mixed-signal IC design, focusing on the implementation of physics-based computing paradigm. The ideal
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
, optimization, and policy modelling. You will also connect with TU Delft's strong internal network on climate action, particularly through the Climate Action Programme and its Climate Governance theme. TU Delft
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Netherlands Application Deadline 15 Nov 2025 - 22:59 (UTC) Type of Contract Permanent Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a
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MSc degree in a relevant field, such as Operations Research, Operations Management, Industrial Engineering, Computer Science, or Machine Learning. Solid experience with quantitative optimization methods
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Systems department. You'll collaborate with an interdisciplinary team working at the intersection of simulation, optimization, and policy modelling. You will also connect with TU Delft's strong internal
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will be determined in collaboration with you based on your strengths and interests, but could for instance involve developing new techniques for efficiently optimizing quantum computations, both in
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Netherlands Application Deadline 1 Dec 2025 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a
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28 Oct 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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. optimization and machine learning techniques) to prepare ports, terminals, shipping companies, and other port actors for this important challenge. Your research will be part of the PortCall.Zero project - a five