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-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
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together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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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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knowledge of statistical techniques for data analysis Experience in detector performance or trigger systems for high energy or nuclear physics experiments Experience with machine learning techniques and tools
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upon future funding. Qualifications Required Education and Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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Previous Job Job Title Post-Doctoral Associate - Electrical and Computer Engineering Next Job Apply for Job Job ID 369523 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
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experiments Experience with machine learning techniques and tools Ability to work in a large international collaboration Hands-on problem-solving skills and clear and concise verbal and written communication
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to science. This is the first large-scale study of its kind, and your results will establish a legacy of scientists working with funding councils to defend their research. Cutting-edge machine learning