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Field
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc: Keystone Project (Machine-Verified LLM Inference) Mission The Keystone project seeks
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leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve how caregiver-child interactions and
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value of these benefits, we have created a tool that calculates the total worth of your compensation package. This tool takes into account all of the benefits that you are eligible for, including health
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related to the project’s objectives. • Process and analyze the collected data by implementing machine learning algorithms and artificial intelligence. • Develop a web-based geospatial interface
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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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characterization (PXRD and Rietveld refinement, SEM, XPS, etc) Experience with machine learning techniques, particularly machine-learned interatomic potentials, in the context of chemical research. Programming
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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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, working closely with the Core Outcome Measures in Effectiveness Trials (COMET) Initiative. You will develop and evaluate natural language processing and machine-learning methods (including large language
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considered. General interest in responsible AI, coursework, use of machine-learning tools, unpublished projects, or publications only in unrelated venues do not satisfy this requirement. For collaborative
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with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction or a related field who enjoy making empirical, methodological, and technical contributions