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open questions in the field live. Research directions include: Using AI to learn parameters and design circuits for quantum optimization algorithms (e.g., beyond QUBO formulations for QAOA) Developing AI
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temporal resolution, spatial resolution, and radiation dose trade against one another, and what semiconductor dynamics can be observed? The primary focus will be on algorithm development, followed by
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temporal resolution, spatial resolution, and radiation dose trade against one another, and what semiconductor dynamics can be observed? The primary focus will be on algorithm development, followed by
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on the development of new diagnostic and prognostic methods (biosensors, biomarker analytics, artificial intelligence), which are expected to be validated via their integration in clinical workflows. The new professor
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process? The primary focus will be on algorithm development, followed by their demonstration at synchrotron experiments. You will start working with real already existing experimental datasets and will have
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candidate has strong analytical skills and programming experience in Matlab, Python, C/C++, or equivalent, and is able and/or eager to develop and implement signal-processing algorithms in such a programming
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on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
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and ETH Zürich, is seeking a practical and motivated engineer to help build the next generation of open foundation models. The successful candidate will help develop and run post-training and
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focus of this new professorship will be on the development of new diagnostic and prognostic methods (biosensors, biomarker analytics, artificial intelligence), which are expected to be validated via
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research collaboration. We are looking for an accomplished, hands-on researcher to lead the development of compact, durable tactile sensors for dexterous robotic hands, so that these hands can manipulate