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Develop algorithms for reconstruction of virtual histopathology images from sparse phase-contrast CT acquisitions of oncological specimens Comparison with standard histology and assessment of algorithm
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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100%, Zurich, fixed-term The Algorithms and Visualization Group in the Social Networks Lab at ETH Zürich is headed by Prof. Dr. Ulrik Brandes. We develop network data science methods
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develop novel learning-based control and policy optimization techniques. We're looking for a skilled machine learning (ML) engineer to develop cutting-edge AI algorithms for digital twin applications in
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application. Develop customized ILC and parameter optimization algorithms for industrial applications, going from theoretical analysis to implementation and testing on real systems Develop adaptive control and
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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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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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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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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
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change, as well as the driving mechanisms A large foundational dataset has already been collected, and presents a unique opportunity for making new insights into debris-flow processes You will develop