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Infrastructure? No Offer Description Work group: PGI-15 - Neuromorphic Software Eco System Area of research: Promotion Job description: Your Job: The conventional, manual co-design of algorithms and hardware is
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science, is looking for a: PhD Candidate, Efficient LLM Algorithm, Hardware and System Design (1.0 FTE) Project description We
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
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benchmarks for these architectures. This will also guide hardware design for such devices and tackle crucial challenges in networked systems and entanglement transmission. Candidate’s profile Knowledge
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8 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer hardware Computer science » Digital systems Engineering
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locally stored internal models of the environment. With existing edge solutions as baseline, a design solution will be explored to cope with the hardware constraints and the impact on energy
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infrastructure. For reduced (CapEx) costs, greater flexibility and faster evolution, mobile core/radio network functions today are largely realised in software over commodity computing hardware in private/public
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into the co-design of ultra-low-power AI hardware architectures tailored for edge computing applications. The research aims to develop neuromorphic processors, FPGA/ASIC-based AI accelerators, and intelligent