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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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topics. Candidates should have some experience working with FPGAs as well as an understanding of computer networks. Experience with both RTL and HLS design is favoured. The ideal candidate would have some
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. During the project, these modules will be emulated by RF FPGA boards designed at the beginning of the project. The first objective of the project will therefore be to propose a very low cost wireless link
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a suit of fast electronics (FPGA) that will allow the following achievements: 1) To rapidly repeat single-particle experimental dynamical trajectories to gain sufficient counting statistics in order
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Postdoctoral Scholar to join the team. The focus of this role is to contribute to the rapidly evolving quantum computing technologies by developing the FPGA based control systems for a wide range of advanced
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. The focus of this role is to contribute to the rapidly evolving quantum computing technologies by developing the FPGA based control systems for a wide range of advanced qubit technologies, including
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. Conocimientos en entornos de programación para control de convertidores: C/C++, Python, VHDL/Verilog para FPGAs o microcontroladores. Habilidad con software de diseño de PCBs como Altium Designer, KiCad, OrCAD o
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, summer schools, and workshops are also covered with the available funding. Eligibility criteria Capacidad para programar sistemas embebidos y diseño digital en HW basado en FPGA. Ability to program
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the available funding. Eligibility criteria Capacidad para programar sistemas embebidos y diseño digital en HW basado en FPGA Ability to program embedded systems and digital design in FPGA-based hardware