50 molecular-modeling-or-molecular-dynamic-simulation PhD research jobs in United Kingdom
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- AALTO UNIVERSITY
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- UNIVERSITY OF SOUTHAMPTON
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- VIN UNIVERSITY
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
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to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
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developments in learning Operator Theoretic representations of dynamical systems that focus on model interpretability, scalability to high dimensions, and data efficiency. The exact direction of the research is
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molecular biology. Relevant post-doctoral experience is desirable. High quality peer-reviewed publications and a keen interest in translational regulation are essential. If you have an excellent background in
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contribute to ongoing cancer risk modelling projects within the Centre for Cancer Genetic Epidemiology (CCGE), based in the Department of Public Health and Primary Care. They should have a strong understanding
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 120 nationalities, 14 000 students, 400 professors and close to 5000 faculty and staff working on our dynamic
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, Physiology and Neuroscience (PPN) in the School of Life Sciences at the University of Nottingham. The role will explore the molecular pharmacology of receptor tyrosine kinases (RTKs), focusing on how
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researchers, molecular biologists and computational microbiologists. Our work is funded by the Ellison Institute of Technology, Oxford Ltd and the pipelines we develop are deployed in https://www.eit
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. Development of DT information modelling, data fusion, and forecasting guidelines and standards, and technology maturity benchmarks to derive cloud platform maturity level standards. Lead on the development