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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
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) is required Desirable Qualifications: Experience with distributed temperature sensing (DTS) Experience with the use of heat as a hydrological tracer Experience with interacting with sensor hardware and
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designing and building hardware solutions, e.g. using Arduino, Raspberry Pi, 3D-printing, CAD and CNC machining and/or laser cutting Language Requirements: Excellent command of English (C1), both orally and
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wall-clock time on available hardware. Thirdly, the quest of generality, namely the ability to simulate a variety of flows within a single software package has been a target in the development
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Experience in simulating fluid mechanics problems using, e.g., COMSOL Experience in interdisciplinary research Experience in designing and building hardware solutions, e.g. using Arduino, Raspberry Pi, 3D
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Physical Layer Security and Hardware Demonstrator Development Physical-layer security is becoming increasingly important for protecting next-generation wireless networks against eavesdropping, spoofing
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. Still, many challenges are ahead. Expanding their impact in real-world deployments requires addressing the heterogeneity of hardware, data, and resource availability in distributed scenarios
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of Technology and QuTech. The goal is to further develop fault-tolerant architectures for photonic platforms based on fusion-based and measurement-based computation, addressing photon loss and other hardware
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programming experience - Strong experience with UNIX/Linux - Familiarity with current hardware and software vulnerabilities and mitigations - Experience with RF and SDR technologies Requirements: BS degree in