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Translation; practical experience conducting data-driven research in a machine translation/large language models (LLM)-related area using a variety of technologies, including eye-tracking; experience as
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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information please visit: https://www.brunel.ac.uk/about/our-history/home We are seeking to appoint a Research Assistant who will work on the ELOQUENCE European project which aims to study Large Language models
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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datasets with machine learning methods, and software development are beneficial Good organisational skills and ability to work systematically, independently and collaboratively Effective communication skills
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, Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning , Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and
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pipeline for learning from a large-scale microscopy dataset. You will work with expert computational scientists, data engineers, and experimentalists to train models that learn foundational embeddings
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” research themes. The successful candidate will have: a PhD in Translation Studies/Machine Translation; practical experience conducting data-driven research in a machine translation/large language models (LLM
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approaches often provide only limited insight into these effects. This project will use advanced computer simulation, informed by post-operative scans and patient movement data, to understand how variations in