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data and archaeological signatures (e.g., circular mounds, linear ditches, rectangular foundations, etc.) tailored for AI applications – Feature engineering and representation learning to enhance
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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the field are foreseen. The job includes participation in (international) conferences and (hybrid) workshops, as well as occasional travel Where to apply Website https://recruitment.jrc.ec.europa.eu/vacancy
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, Physics, Electrical Engineering, Communication Engineering, or equivalents; – Knowledge in artificial intelligence, statistical and machine learning, complex systems, agent-based modeling and simulation
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) project MicroMan4Health (website: https://www.microman4health.eu/ ), Data-Centric Micromanufacturing Platform Towards Added Value in the Health Sector. The shift from process-centric to data-centric
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, Italy, SSM is a prestigious institution of higher learning and research with a deeply rooted interdisciplinary approach and a global perspective. Renowned for its rigorous selection process, SSM admits
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2026/2027, subject to obtaining ministerial accreditation pursuant to Ministerial Decree 226/2021. Where to apply Website https://unifg.esse3.cineca.it/Home.do Requirements Research FieldBiological
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nanocrystals, hybrid perovskites and 2D materials. Development of new data-driven approaches for studies of optoelectronic properties using EM, including machine learning / machine vision algorithms. The balance
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international secondments, network-wide training events, and interdisciplinary research activities Acquire highly sought-after expertise in microfabrication, photonics, materials science, and optical sensing