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Overview Dr. Hana Aliee wishes to recruit a student to work on the project entitled: Generative Modelling for Foundational Discovery in Biomedicine. For further information about the research group
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of Computer Science and Technology at the University of Cambridge, UK. This position is part of a broader effort to advance fundamental research in classical and quantum complexity theory. The successful candidate will
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
present at top AI/ML venues and validate ideas on real platforms. Mentorship focused on visionary brainstorming, in-depth technical discussions, and collaborative work culture on both theory and systems
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to increase each year. We recommend that you apply early as the advert may be removed before the deadline. A modern area of research within probability theory is the study of a class of models named after
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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. A modern area of research within probability theory is the study of a class of models named after Kardar, Parisi and Zhang and referred to as KPZ. This includes mathematical models for the random
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-resolution metagenomics and work with population genetics theory. This will cumulate in a new understanding of host-microbial interactions through acclimatization and adaptation, that will be validated in
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theories and models. This project aims to develop new insights into how bedrock incision processes interact with geological and climatic factors (i.e. spatially variable uplift, shield building, mega
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widely, to advance theoretical understanding, and to introduce original theory. The candidate, while based in a Marketing Department, will work within an interdisciplinary research environment – the Centre
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depend on the candidate’s skills and interests, but may include genetically engineering microbes to change form and function (if the candidate has a strong biological background), developing theory and