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Field
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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Responsibilities Develop suitable algorithmic methods for live and real-time analysis of synchronous and asynchronous data. Write research reports and publications. Analyse and interpret the results of own research
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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with radioactive sources and at beamlines to test the performance of the NOVO prototype. Contribute to the development and testing of AI-algorithms for image reconstruction. Support NOVO staff working
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undergraduate students during summer months. Apply existing remote sensing based algorithms, such as 3T, to estimate latent heat fluxes from thermal imagery and soil water balance. Develop and test upscaling
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undergraduate students during summer months. Apply existing remote sensing based algorithms, such as 3T, to estimate latent heat fluxes from thermal imagery and soil water balance. Develop and test upscaling
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Automation group will develop novel machine-learning based control algorithms that allow for real-time adjustment of OSA therapy. The main challenge is to develop robust machine learning algorithm which can
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, at the University of Cambridge, UK. The Research Assistant will work together with a team of students and research collaborators on the development of learning-based control policies that facilitate
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to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
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implementation of various projects, including (but not limited to) scaling, algorithm development, scaled score development and documentation. Support the creation, management, and retention of large-scale data