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to multi-task learning for multi-cancer risk prediction. To develop these models, you will have access to unique biobank data containing genetic information linked to Danish registry data for approximately
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stakeholders and an analysis of TIA clinic data you will help to understand how stratification might assist in delivery of more appropriately targeted care. You will develop mixed-methods expertise and join Dr
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role in supporting data-driven, policy-relevant research examining energy markets and a range of associated social and environmental challenges. This role is ideal for candidates planning to apply to top
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research within the framework of the funded program. This project seeks to research, locate and reveal peoples’ experiences of polio to link personal accounts to the meta-narrative of health and illness
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you can become part of our community. You will be employed jointly by the Department of Mathematics external link and the Department of Information and Computing Sciences external link . Within
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Project Link: Image guided intervention supported with mixed reality | Project Opportunities | PhD | University of Leeds Eligibility: UK and International Funding: School of Computer
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and experimental data, the student will develop predictive models of strand displacement reactions in non-ideal settings, in collaboration with the other students within BIOHYBRITE. These areas include
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, the projects combine classical microbiology, microbial physiology, experimental evolution, and omics-based approaches to link microbial interactions and system performance across spatial and functional scales
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project is funded by the Center for Pharmaceutical Data Science Education (CPDSE) and will be conducted under the supervision of Associate Professor Casper Steinmann . The project concerns physics-based
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and to link outputs from meteorological macroscale models to microscale load effects on buildings and structures. The model will be used to simulate a wide range of weather conditions – from severe