303 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" Postdoctoral positions in United Kingdom
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The Role The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data
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and clathrin (PMID: 29921601 and BioRxiv https://doi.org/10.1101/2025.08.20.671218). Septins act as a restriction factor that suppresses viral release from the cell, while clathrin enhances viral spread
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that promote economic welfare. For more information about the Georgetown Center for Business and Public Policy, visit http://cbpp.georgetown.edu . APPLICATION PROCEDURE Application materials should be sent by
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trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data. The successful candidate will contribute to understanding how modern machine
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. The opportunity: We are looking for someone to analyse environmental soundscapes using signal processing or machine learning. Initially, you will work with underwater passive acoustic sound data, and later may
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/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field. You will have an excellent academic track record in topics relevant to locomotion and manipulation; path
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using liquid biopsy next generation sequencing data for cancer diagnostics. About You Must have a strong background in next generation sequencing data analysis/machine learning, cancer and/or genome
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The University of London The University of London is both the UK’s largest provider of international distance and online learning and the convenor of a federation of 17 renowned higher education
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fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC
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“Quantifying Efficacy and risks of solar radiation management (SRM) approaches using natural analogues”. The project will use novel machine learning-based methods to determine the climate response to a range of