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neural network types for efficient hardware implementation Developing an FPGA-optimized design Performing device-aware training using both simulated and measured datasets Validation of the complete
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for dedicated implementations of latent reasoning. These investigations will be grounded in hardware through co-design of neuromorphic hardware to improve accuracy, latency, data efficiency, and energy
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that you meet the following essential criteria: Have a relevant MSc in Electrical and Electronic Engineering/Computer Science (or related discipline). Good hardware / software design skills. Good
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RF circuits in Python Validate the developed models against circuit simulations and measurements Perform hardware-algorithm co-design for AI-driven 6G transmitters Publish and present your results at
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models of analog and RF circuits in Python Validate the developed models against circuit simulations and measurements Perform hardware-algorithm co-design for AI-driven 6G transmitters Publish and
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others of the following tasks: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization
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environmental monitoring, search and rescue, and early-warning services. The work spans protocol design, embedded firmware on STM32WL hardware, and large-scale evaluation through network simulation, and it
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, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ Project description The project focuses on the design and analysis of modes of operation for symmetric-key cryptography
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ASIC design and/or SDR platforms(e.g., Zynq SoC, RFSoC,) Knowledge of fixed-point design and hardware constraints Strong programming skills (C/C++, Linux environments) When interested in the higher
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Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | about 2 months ago
sit at the interface between the classical and quantum worlds. You will design QEC codes suited to realistic hardware, develop the decoding algorithms that make them practical, and map the trade-offs