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PhD position in Experimental Physics with focus on photonics and materials science (applied aspects)
education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Physics at Umeå University (https://www.umu.se/en/department-of-physics/ ) conducts strong
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for Scientific Research), Grenoble-INP (Grenoble Institute of Technology), and the University of Grenoble, affiliated with Inria (French National Institute for Research in Digital Science and Technology) and the
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on https://www.heliabiomonitoring.com/publications . The research group integrates laboratory-based and computational approaches for advancing sensor technology and bioengineering. Research is done in close
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network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial electrical
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(m/f/d) in the field of Ultrafast Chirality for Life and Technology (EU MSCA Project TRILOGY) Job profile: The EU-funded Horizon Europe Doctoral Network TRILOGY advances the emerging field of ultrafast
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promising topology for driver and TIA in advanced semiconductor technology Where to apply Website https://www.academictransfer.com/en/jobs/364085/phd-in-the-integrated-circuit-g… Requirements Specific
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successfully completed a master's degree in (applied) economics, econometrics, finance or business administration or business engineering by September 2026. Successful candidates should have excellent
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning and neural networks Basic
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15th October 2026 Languages English English English The Department of Information Security and Communication Technology has a vacancy for a PhD Candidate in Cyber Risk Management in Maritime
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optimization engines for memory-aware deployment, compiler and runtime systems capable of supporting dynamic neural network topologies, energy-efficient embedded AI frameworks targeting RISC-V multicore and