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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 7 days ago
for a LIBS spectrometer: laser control; carriage and galvanic mirrors control; spectrometer development; power supply. The spectrometer module will feature a STM microcontroller and a FPGA with a USB-3
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a suit of fast electronics (FPGA) that will allow the following achievements: 1) To rapidly repeat single-particle experimental dynamical trajectories to gain sufficient counting statistics in order
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attacks on QKD sources or single-photon detectors. Experience with microelectronics, fast signal processing, and circuit design, including FPGA-based control, real-time acquisition, and hardware description
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simulations on superconducting processors for physics, chemistry, and computer science. Firmware development & programming tools to interface with FPGA-based electronics. Quantum verification and validation
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significant prior experience of: power semiconductor switching converters such as oscilloscopes programming MicroSemi FPGAs in the Libero environment low level programming of embedded C++ in Infineon Tricore
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(e.g., hardware trojans, side-channel exposure). Co-develop testbenches for hardware simulations and chiplet-level threat modelling. Collaborate closely with FPGA and IC prototyping teams to deploy AI
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activities will be developed in the Power Electronics area, focusing on programming control algorithms on a Xilinx FPGA. This project aims to implement internal fault tolerance in a power electronics
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development proposals and funding bids. The successful candidate will have significant prior experience of: power semiconductor switching converters such as oscilloscopes programming MicroSemi FPGAs in
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hardware design (Verilog/VHDL), FPGA-based acceleration, etc. Experience with deep learning frameworks like PyTorch, Keras, or TensorFlow, and tools such as Jupyter Notebook, is expected. A strong foundation
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coarse grained reconfigurable arrays (CGRAs), virtualisation of FPGAs using partial reconfiguration, and accelerator support for machine learning. Postdocs at KAUST enjoy generous salaries and free