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rooms in the Nordic countries are located in the Micro- and nanotechnology centre Micronova. Doctoral Researcher in Hardware-Aware AI for Analog and RF Circuits. We are now looking for a Doctoral
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constraints into the theoretical analysis. Provide design guidelines for future experimental implementations of quantum repeater networks, specifying hardware requirements and performance benchmarks. Contribute
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. Programming, coding, and experimental hardware skills (desirable). Strong analytical and mathematical capabilities. A passion for research and a willingness to learn. Excellent presentation, communication, and
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. Programming, coding, and experimental hardware skills (desirable). Strong analytical and mathematical capabilities. A passion for research and a willingness to learn. Excellent presentation, communication, and
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/coding and experimental hardware skills are desirable. Strong analytical and mathematical skills. Passion for research and willingness to learn. Good presentation, communication and scientific writing
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Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A
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modern machine learning, statistical signal processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs
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have, rather than requiring costly new hardware. Working within a multidisciplinary supervisory team spanning quantum, post-quantum and classical cryptography, you’ll gain hands-on experience in an area
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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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, ICML). Students receive regular guidance, research training, publication support, hardware/compute access and Intel engagement opportunities. Entry requirements: Relevant undergraduate or master’s degree