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Field
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be the following: Characterise a uLED array by using microcontroller – FPGA; Design of the controlling and driving circuit of the uLEDs array by using 180nm CMOS technology; Integrate the uLED array
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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
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for advanced sensing applications and the design of embedded readout architectures based on FPGAs or microcontrollers for signal acquisition and processing. The activities will include electro-optical and
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and decoding information from neurons Prior experience dealing with custom hardware, FPGAs, and using/writing APIs to communicate with the hardware Like to live in the intersection of biology, hardware
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(especially neuromorphic) device, circuit and system design, clean-room fabrication, ferroelectric (or antiferroelectric) materials and devices, memristors, tactile sensors, FPGA/MCU/API development, machine
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FPGA-based platforms (preferred). Mandatory Qualifications Education MSc in Electrical Engineering, Applied Physics, or a related field with a focus on Hardware development. Experience and Technical
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exposing hardware accelerators, such as GPUs and FPGAs, in a seamless and portable way. This includes designing execution logic and resource-scheduling strategies that make efficient use of available
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hardware design and verification (HDL: VHDL/Verilog, simulation tools). · Hands-on experience with FPGA prototyping or hardware/software co-design is highly desirable. · Good communication
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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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circuits in field-programmable gate arrays (FPGAs). Includes the basic building blocks of FPGA programming, architecture, best design practices, error-free design, and optimizations of finite state machines