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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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, microelectronics (such as FPGAs and ASICs), Artificial Neural Networks, AI and Machine learning, cubesat activities, wireless technologies and all technologies related to the EEE component family (such as Si
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analysis) and FPGA design. Where to apply Website https://www.academictransfer.com/en/jobs/349526/phd-position-on-hardware-securi… Requirements Specific Requirements You are an enthusiastic and highly
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, microelectronics (such as FPGAs and ASICs), Artificial Neural Networks, AI and Machine learning, Cubesat activities, wireless technologies and all technologies related to the EEE component family (such as Si
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, microelectronics (such as FPGAs and ASICs), Artificial Neural Networks, AI and Machine learning, Cubesat activities, wireless technologies and all technologies related to the EEE component family (such as Si
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-route to GDS, ensuring that design specifications meet performance and energy efficiency targets. Hardware Testing: Engage in PCB design and FPGA programming to validate the system and contribute to a
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an asset. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process. Experience of working on a cubesat project, FPGA