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you passionate about brain-inspired AI and sustainable tech? As a PhD Candidate, you will design real-time FPGA-based systems that mimic neural processes, enabling intelligent, on-chip learning for edge
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 3 months ago
, leading to a substantial overhead in execution time and energy efficiency [3]. Modern field-programmable gate array (FPGA) with their on-chip URAMs and BRAMs, as well as access to high-bandwidth off-chip
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. Specific requirements of the candidate Applicants should have a strong background in cryptography, FPGA design, or embedded systems. Experience with hardware design (e.g., Verilog/VHDL), post-quantum
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and familiarity with hardware description languages such as VHDL, as well as experience with FPGA development environments like those from Xilinx or Microchip, would be an asset. In addition
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-level knowledge in FPGA/hardware design using hardware description languages and/or high-level synthesis (VHDL, Verilog, Vitis HLS, Vitis), and experience in programming FPGA boards. You have basic
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serverless computing, data center networks, programmable networks, and FPGA acceleration. Where to apply E-mail lin.wang@uni-paderborn.de Requirements Research FieldComputer scienceEducation LevelMaster Degree
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the research, focusing on both component-level solutions and algorithm optimization. The chosen solution will typically be implemented on a microprocessor platform, with the possibility of using FPGA
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platform, with the possibility of using FPGA for specific functions as appropriate. The project will provide an overview of the research front with regard to energy-efficient signal processing but also
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for the integration of heterogeneous systems with large chips. Thus, we propose this thesis project to develop a novel approach for process (FOWLP) to integrate heterogeneous active chips (HBM, ASIC) and passive
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, electromagnetics, or RF engineering. Ability to take initiative and drive innovative research. Proven skills in scientific writing and publication. Experience with Xilinx FPGAs, microcontrollers, or RF circuit