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Field
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postdoctoral Research Fellow (RF) position for one year with a possible extension for one more year. The starting date is November or December 2025. This post will advance the application of Machine Learning (ML
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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, Recommender Systems, Machine Learning or Artificial Intelligence (applied to text or financial data) A3 A comprehensive and up-to-date knowledge of the wider subject area or subject specialism in Information
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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 can be
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research into planet formation/protoplanetary discs or the ISM/star formation and may also have some experience in statistical methods and/or machine learning. Dr Winter and QMUL are committed to improving
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the requisite experience. Desirable: B1 An awarded (or recently submitted or near completion) PhD in subject specialism or equivalent. B2 Experience with high dimensional statistical, machine learning and deep
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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analysis and machine learning methods for optimisation and decision making, to describe the F&V supply chains for various products at regional UK scale and assess their resilience to cascading risks
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal