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assist the research progress of doctoral students towards graduation without delays, thus ensuring an optimal graduation time of four years for PhD candidates. Because of the close ties with the research
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highly motivated PhD researcher with an interest in optimizing distributed ML models for resource-constrained devices. The applicant should: have a master’s degree in Electrical Engineering or
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. The PhD candidate will combine materials science, computational modelling to design a novel framework that identifies optimal materials and AM processes based on performance, sustainability, and reusability
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Electrical Power Engineering and Mechatronics. The Proposed PhD thesis topic: “ AI-Driven Battery Life Optimization for V2X-Enabled Software-Defined Vehicles ” Supervisors: Sup. Researcher Dr. Hadi Ashraf Raja
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in a strongly heterogeneous setting (e.g., CPUs+GPUs). Additionally, this work can benefit from the developments of WP1 and WP2 of Exa-SofT around the development of optimization techniques
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. Responsibilities and tasks This PhD project aims to optimize the design of hybrid electrical–optical computing architectures: Investigate and design optimal computing and communication architectures for hardware
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will be dedicated to optimizing the searches for high-frequency gravitational waves in a network of electromagnetic cavities, or other setups to be conceived during the project. All aspects, from source
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Stig Brøndbo 6th February 2026 Languages English English English Faculty of Science and Technology PhD Fellow in Nanophotonics Apply for this job See advertisement The position Are you keen on
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of this joint laboratory is towards the development of innovative nanotechnologies and nanomaterials for various electronic and photonic applications. For more details, please view https://www.ntu.edu.sg/cintra
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous