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underlying mutation biases alongside fitness landscapes. BioRxiv. doi: 10.64898/2026.07.06.736753 Lytras S, Ghafari M, and Grove J (2026) Studying the Deep Evolution of Viruses in the Era of Artificial
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: Reference Number 11336 Artificial intelligence (AI) methods have the potential to significantly advance and transform Earth system sciences, particularly given the complexity of the Earth system as a dynamic
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: Reference Number 11340 Artificial intelligence (AI) methods, particularly generative AI, have the potential to significantly advance and transform Earth System Sciences (ESS), especially given the complexity
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curious to deliver work that matters, your journey starts here! The Machine Learning Department (MLD) at Carnegie Mellon University is a leading hub for research and education in artificial intelligence and
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biomedical research. The successful candidate will collaborate within a multidisciplinary research environment at the intersection of artificial intelligence, structural biology, and bioinformatics, advancing
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of the job description. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible. Artificial
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Computational Neuroscience and AI (CNAI), led by Professor Alexander Mathis, is seeking two postdoctoral fellows to join our team working at the intersection of artificial intelligence and neuroscience. Our
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, while postdoctoral applicants are expected to have a strong publication record in machine learning, artificial intelligence, optimization, or related areas. Excellent communication skills and fluency in
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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to promote the industrialization of technology. ESSENTIAL QUALIFICATIONS/EXPERIENCES A Ph.D. (obtained or soon to be obtained) in Computer Science, Automation, Artificial Intelligence, Operations Research