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Models (LLM) to query and reason geospatial data. The project aims to develop a pilot decision support systems in collaboration with industry partners. The Postdoctoral Research Fellow will undertake
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, defensive mechanisms and related topics to the safe deployment of systems contain multiple LLM and VLM powered models. You will be responsible for Developing and implementing; capability evaluations, attacks
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the cellular and molecular mechanisms driving tumour development. In this role, you will support a team of scientists using genetically engineered mouse models (GEMMs) and transplantable tumour models (e.g
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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are working to set up a new,human challenge model ofStaphylococcus aureus skin infection. This model will be used to study the early interactions between the human immune system and invading bacteria. From
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. The study will involve the use of iPSC-based models to elucidate molecular mechanisms and biosamples from patient cohorts to validate biomarkers. As such, the post will offer an excellent opportunity
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work on the development and implementation of machine learning models aimed at detecting urban drainage infrastructure components (such as stormwater drains, sewers, and manholes) from publicly available
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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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Our lab (https://www.cruk.cam.ac.uk/research-groups/biffi-group ) combines ex vivo human and murine pancreatic tumour organoid/fibroblast co-cultures with murine in vivo models and patient-derived
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly