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approaches, including advanced live cell imaging and in vitro motility assays. The position is based in Michael Way’s laboratory at the Francis Crick Institute. Click here to read more about the Way lab
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following areas: foundation models, multimodal learning, LLMs, AI agents, or trustworthy AI. Proficiency in Python and PyTorch Responsibilities Research Conduct independent and collaborative research in
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controllability • Learning and calibration strategies for uncertainty-aware language model prediction • Knowledge-augmented and neuro-symbolic approaches for language-based reasoning • Evaluation and design of LLM
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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spatio-temporal generative models, and multimodal foundation models—including vision-language MLLMs and agentic AI frameworks—for longitudinal MRI and clinical data. Fellows will help build next-generation
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, and Experience - PhD in Computer Science, Computing, Statistics or Data Science, or related disciplines - Demonstrated hands-on experience training, fine-tuning, or adapting LLMs / generative AI models
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
their assigned duty station. The Data-Driven EnviroLab (DDL) is an interdisciplinary and international research initiative based at UNC’s IE that is redefining how data is used to tackle the world’s most pressing
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MD or PhD or equivalent degree and has interests in immunotherapy and/or hematopoietic stem cell transplantation using mouse animal models. The research involves understanding the mechanisms underlying
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or adaptive systems reinforcement learning, multi-agent systems, network or graph-based models simulation of complex socio-technical or organisational systems causal inference, econometric analysis, or formal
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Framework (RDF). enables advanced data mining queries using the SPARQL query language. provides a natural language-based interface to perform these queries on the knowledge graph using a large language model