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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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libraries. Experience with modern deep learning frameworks (e.g., PyTorch). Experience in using Large Language Models in real-world use cases. Experience in working with large datasets. Knowledge
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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Computing, Engineering and the Built Environment (On-site) Machine Learning R&D Engineer (KTP Associate) Fixed Term: 18 months Salary range: £45,000 - £55,000 per annum Location: Buro Happold Limited
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at the Institute of Genetics and Cancer. Informal enquiries may be directed to Dr Athina Spiliopoulou (A.Spiliopoulou@ed.ac.uk ). Your skills and attributes for success: PhD in machine learning, genetic epidemiology
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Aalto University is looking for an Postdoctoral Researcher in Artificial Intelligence / Machine Learning Engineering [Academic Research Software Engineer] to a postdoctoral-level position. The
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fantastic opportunity for ambitious computer scientists to join our Computer Science Graduate Teaching Assistant (GTA) Programme! How does it work? Candidates will study for a four year, full time funded PhD
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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