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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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manipulation of ultracold gases. Examples include basic electronics, development of FPGA devices, development of narrow-linewidth lasers, laser frequency stabilisation and control, image analysis, data
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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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provide a performance or efficiency advantage, and determine scenarios where conventional AI accelerators (such as embedded GPUs or FPGA-based accelerators) remain more appropriate due to data
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Engineering). Our partners and funding projects provide access to hardware testbeds, such as RISC-V vector processors, ARM-SVE processors, x86 clusters, FPGAs, etc. As a postdoctoral researcher you will be