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Applicants are invited for the posts of Postdoctoral Research Associate or Research Fellow in Machine Learning to work with AI Researchers in the Centre for AI Fundamentals at the University
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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standard public holidays and an additional 4 days including the closure of our office between Christmas and New Year Location: Hatfield, Hybrid We are seeking a full-time Research Fellow on Machine Learning
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data to address priority questions in cancer care pathways, diagnostic delay, and treatment access. The role will involve advanced quantitative analyses, such as survival modelling, machine learning, and
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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not yet competitive for 5-year clinician scientist fellowships. This post is designed for applicants with a research interest in machine learning or data science approaches for patient stratification
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large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
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of subsurface processes. You will be responsible for leading the development of the approach, which could include transferring learning from other geographic regions and data types, machine learning methods