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of synchronous sequential circuits, state machines, FPGAs, memories, arithmetic circuits, and computer-aided design. Laboratory involves CAD-based design implemented on a FPGA including elementary interfacing
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development. Experience with DSP/FPGA/Microcontroller/Microprocessor (such as Raspberry Pi) platforms for controller development. Network and develop collaborative R&D with other groups and divisions internally
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with FPGA programming used in superconducting quantum circuit experiments. Model-Free Quantum Control via Reinforcement Learning: Reinforcement learning (RL) is an emerging approach for optimizing
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
cameras, FPGA-based frame grabbers, SDI-based interface cameras, Arduino controllers, motorized stereo rigs, etc.). We are looking for someone with hands-on experience who is enthusiastic about computer
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learning on microcontrollers (MCUs), and FPGA-based design, and who has a genuine passion for project-based learning and mentoring both small and large student projects. Research Focus: The postdoctoral
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scientific research. Typical systems integrate PLC and FPGA hardware platforms within the EPICS framework. As a member of the team, you will work closely with control system engineers and accelerator operators
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Engineering, Telecommunications Engineering, or a closely related field. SDR Expertise: Strong hands-on experience with SDRs (USRP, RFSoC, or equivalent). FPGA programming experience is a plus. Programming
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built around Field Programmable Gate Array (FPGA) technology. Self-motivated, with demonstrated ability to apply professional engineering judgement in the course of deployment, commissioning, maintaining
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(such as FPGA, DSP and CPU), including ASIC/FPGA/IP core usage and development and verification processes and languages (such as VHDL, Verilog); high-speed data conversion (A/D and D/A) techniques and
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optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a