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Field
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decision-making, computational efficiency, generalization under changing market conditions, and safe constraint handling. The PhD candidate will develop and validate decision-support methods based on deep
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accordance with the MSCA-DC program. Have a Master’s degree in a relevant field (e.g. Artificial Intelligence, Computer Science, Data Science, Mathematics, Engineering or relateddisciplines). Demonstrate
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Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence
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This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing
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to the requirements of the position. Required selection criteria You must meet the requirements for admission to the faculty's Doctoral Programme , see Section 6-1 of the PhD regulations for more information. You must
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
1st October 2026 Languages English English English The Department of Mechanical and Industrial Engineering has a vacancy for a PhD Candidate to conduct research on Artificial Intelligence
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program 2) a detailed CV, 3) your grades, 4) a summary of your MSc/PhD thesis and list of publications (if any). If the applicants are selected for an interview, they will be asked to provide contact
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conferences and journals, participate in European research collaborations, undertake international secondments where applicable, and benefit from TU Delft’s PhD training programme, technical courses, and
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Are you inspired by developing the next generation of intelligent photonic chips? Join us to pioneer heterogeneously integrated photonic technologies for ultra-fast, energy-efficient optical