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to apply Website https://www.academictransfer.com/en/jobs/359150/phd-position-digital-ai-chip-de… Requirements Additional Information Website for additional job details https://www.academictransfer.com
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Enhancing the Resilience of Offshore Wind Electrical Systems through Digital Twin Tools Offshore Wind CDT PhD Research Project Directly Funded UK Students Dr Antonio Griffo, Dr Xiao Chen, Dr
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operations implemented via high-speed FPGA processing. We are seeking a highly motivated and skilled Postdoc to join our cutting-edge research in synthetic dimensions. Within this position, you will create
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electronics for sensor readout systems, including ASIC and SoC design and verification. Strong experience in hardware–firmware co-design for data acquisition and processing pipelines, including FPGA-based
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-design with accelerators (FPGAs, GPUs, near-memory systems) to achieve real-time, energy-efficient AI for high-tech industry applications. Work with leading companies like ASMPT and shape the future of AI
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). Knowledge of computer architectures. Knowledge of embedded systems. Knowledge of developing systems with systems-on-a-chip (SoC) and FPGAs. Knowledge of scheduling is desirable. Motivation to pursue a
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programming and code porting on accelerators (FPGAs, GPUs) are being developed, as well as the development of RISC-V applications in scenarios where the use of open hardware is necessary. Another research topic
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-year fellowship-program offers excellent researchers who have recently completed their PhD the chance to continue their research career at CTU. Fellows receive a two year fellowship and become members
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PhD students, postdocs, and faculty on joint projects, ensuring experimental results support theoretical work. Co-author scientific publications in IEEE journals and conferences, and contribute to open
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project The main objective of this PhD project is to explore and analyze bio-inspired neural architectures for early detection from spatio-temporal data under realistic sensing and computational constraints