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Field
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based platform for the interactive and comprehensive evaluation of design solutions and mitigation strategies
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, first on whether these indeed drive these aberrant states, and second on whether these indeed drive the growth pattern. You will be embedded both within an experimental and computational team, providing a
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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expertise in sensor design, experimental testing, modelling, machine learning, and industrial collaboration, positioning you to contribute directly to next-generation inspection technologies for aerospace
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channel. This will be followed by designing a new resilient waveform for UOWC and developing a computer-based simulation to evaluate its performance. Finally, the study will use existing UOWC channel
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multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to optimize the design of hybrid electrical–optical computing architectures
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PhD Stipend/Integrated Stipend in representation, compression, learning, and inference for classical and quantum data. At the Technical Faculty of IT and Design, Department of Computer Science, one
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seeking a PhD candidate in computer architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators
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FieldTechnology » Computer technologyEducation LevelMaster Degree or equivalent Skills/Qualifications Must hold a Master’s in Electrical Engineering, Computer Science or Computer Engineering. General computer