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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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, single-atom catalysts), analytical instrumentation (including electronics and LabVIEW FPGA programming), finite element modelling using COMSOL Multiphysics, and in-situ/operando spectroscopy, among other
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know the fundamentals of quantum computing. It is also expected that the participant has knowledge to work on diverse software and hardware (knowledge on working with FPGAs and ASICs will be preferred
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for seizure detection. These algorithms will be implemented on a spiking neural network (SNN) processing unit deployed on FPGA and custom-designed chips with an integrated detection mechanism. Research area and
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, PSIM, Proteus, LabVIEW, SketchUp, SolidWorks, etc. Knowledge of microcontrollers, STM32, FPGAs, etc. Knowledge of communication protocols such as I2C, SPI, Profibus, Modbus, CAN, MQTT, and HTTP
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., GNURadio, Matlab, LabView), and/or FPGA development (e.g., VHDL) is a plus. You are a team player and have strong communication skills. You have a high proficiency in oral and written English. You comply
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in advanced firmware design for state-of-the-art FPGA architectures. The role involves working with industry-standard tools (e.g., Intel Quartus or AMD Vivado, Modelsim/Questa), implementing high-speed
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, single-atom catalysts), analytical instrumentation (including electronics and LabVIEW FPGA programming), finite element modelling using COMSOL Multiphysics, and in-situ/operando spectroscopy, among other
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communication skills. · Skills relevant to the trapping and manipulation of ultracold gases. Examples include basic electronics, development of FPGA devices, development of narrow-linewidth lasers, laser
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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied