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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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reinforcement learning and other approaches for cross-domain generalization Qualifications Essential: PhD in Computer Science, Machine Learning, Computer Vision, Natural Language Processing, or closely related
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reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
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Description The Robot Learning & Control Lab (REAL Lab) at NYU Abu Dhabi is seeking an outstanding Post-Doctoral Associate to contribute to cutting-edge research in robot intelligence, machine
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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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(IDP), conduct research studies, attend required courses/seminars, write grants, publish manuscripts, present oral presentations locally and nationally, and learn other skills necessary for a successful
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 18 hours ago
-Neptunes and gas giants (3 years). Developing next-generation techniques for atmospheric characterization through retrievals with machine learning, including techniques such as simulation-based inference