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Field
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good programming and automation skills (e.g. C++, MATLAB, Python, LabVIEW, Arduino, Raspberry Pi or FPGA-based controllers) Expertise in developing robotics and motion control systems is beneficial
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virtual reality systems, code language models, high-level synthesis, Bayesian neural networks, and FPGA-based acceleration. To apply as a Research Associate you must have a PhD (or equivalent) in
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that integrate analog/digital architectures with neuroscience-inspired algorithms Implement and optimize biologically plausible learning rules on FPGA and high-performance computing (HPC) platforms Basic
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accelerators and other scientific applications, focusing on FPGA-based digital signal processing for real-time control. Responsibilities span the full system lifecycle, from concept to commissioning, with
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acquisition systems for particle accelerators and other scientific applications, focusing on FPGA-based digital signal processing for real-time control. Responsibilities span the full system lifecycle, from
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optimization, and calibration methods. Digital logic design and implementation using FPGAs. Experience in DSP programming and interfacing. Programming in C++, UNIX, Python, Matlab, and familiarity with image
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systems including bare-metal embedded systems, RTOSes, FPGAs, and embedded Linux. You will have opportunities to develop tools, techniques, and processes to solve some of the most difficult software
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effectively with a range of stakeholders. Experience working with a range of computer systems and applications, including microwave/microelectronics and low-level software languages such as C/C++ and/or FPGA
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should also be able program, at a basic level, hardware which utilises FPGAs and small embedded processors; these devices are increasingly being used for teaching/research within Electronic Engineering
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experience or equivalent. • Knowledge with building embedded control systems in Python or C++/C#. • Experience in machine vision and/or industrial automation. • Experience with PCB design, DAQ, and FPGA