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Field
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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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undergraduate students, and technical personnel at the ElectroScience Laboratory (ESL); Leads and advances research and development on systems requiring the use of Field Programmable Gate Arrays (FPGAs); designs
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 9 days ago
supply for the WFI camera with numerous different and noise-sensitive analog voltages to FPGA-based control electronics including the understanding and functional and verification testing of an externally
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of experience preferred, but fewer years may be considered if relevant. Proven skills in PCB design, FPGA development, and signal processing. Proactive, organized, and comfortable working in a multicultural
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signal processing, and FPGA readout systems. Teach undergraduate and graduate courses related to semiconductor devices, analog electronics, signal processing, and FPGA-based systems. Mentored graduate
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(e.g., hardware trojans, side-channel exposure). Co-develop testbenches for hardware simulations and chiplet-level threat modelling. Collaborate closely with FPGA and IC prototyping teams to deploy AI
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Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
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on hardware which may include CPUs, GPUs and FPGAs. In particular we are interested in applicants who have experience of modern coding practices and software techniques. The post-holder will work with Prof. Ben
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Neuromorphic and AI-Optimized Processors – Design AI-specific chip architectures, including neuromorphic and domain-specific accelerators (TPUs, NPUs, FPGAs), for low-power and real-time AI processing. AI-Driven
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line