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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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opportunities for embedding storage at multiple points within the HVDC architecture—on the AC side, DC side, or directly within converter submodules. The research will tackle several key technical, economic, and
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques
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identifying suitable ultrasound technologies for muscles with varying architectures, integrating recording hardware, and establishing acquisition protocols to capture both electrical and architectural
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engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL, SystemC), reconfigurable architectures (e.g. FPGA, CGRA) What we expect from you: above-average degree
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Requirements: excellent university degree (master or comparable) in computer engineering or electrical engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL
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reusable launchers, autonomous robotics, and advanced materials could redefine how we design space structures. The ability to remotely assemble orbital systems from multiple launcher payloads would allow
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in the Power Electronics Group at UT and collaborate with experts from Seine Batteriesysteme, NRG2Fly, and multiple airports. The project also supports open-source developments in MW-charging protocols