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Multiple Tenure-Track Assistant Professor Positions in Microelectronics, Circuits and Systems Design
can teach and lead research in one or more of the following areas: analog and mixed-signal integrated circuits; digital VLSI and AI hardware systems; advanced packaging and heterogeneous integration
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Photonic Integrated Circuits (PICs) in Europe. These projects strengthen ICFO’s strategic positioning across the entire PIC development pipeline — from design and fabrication to packaging, testing
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dot materials, photonic integrated circuits and optoelectronic devices on silicon for future communication, sensing and information-processing technologies. Building on pioneering demonstrations of
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and lead research in one or more of the following areas: analog and mixed-signal integrated circuits; digital VLSI and AI hardware systems; advanced packaging and heterogeneous integration; and power
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and lead research in one or more of the following areas: analog and mixed-signal integrated circuits; digital VLSI and AI hardware systems; advanced packaging and heterogeneous integration; and power
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. These devices will be linked into photonic circuits to form the basis for optical computing applications. Specifically, projects in the lab include (1) developing new integrated optical device designs via
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techniques and adapt them to operate within a low power consumption framework, in collaboration with the integrated circuit design team (CMOS technology) • Draw up a set of specifications for the overall
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opportunity is sponsored by SONY. Where to apply Website https://phd.fbk.eu/calls/detail/self-mixing-interferometry-integrated-sensor-an… Requirements Research Field Other Education Level Master Degree or
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-integrated III-V modulators. At imec, we develop advanced integrated-photonics technologies for next-generation optical interconnects, computing, communications and sensing. We are looking for an R&D
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initiative focused on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data