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publications, and collaborate with academic and industry partners to advance fundamental and applied polymer science. This position offers an exciting opportunity to work in a leading research environment with
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; to collaborate on research publications and present at conferences; and to help deliver the project's one-day workshop for the GLAM, digital humanities and AI communities. You will report to the Principal
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agencies, technology partners, and the World Health Organization. This is an exciting opportunity to join a highly collaborative, multidisciplinary research environment at the forefront of AI and global
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and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental immunology allows us to tackle fundamental biological questions with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly
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communication. Ability to work effectively in a collaborative research environment. Preferred Qualifications: Experience with mouse behavioral assays and motor learning paradigms. Experience with two-photon
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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, cognitive psychology, or a related field. You demonstrate strong collaboration skills and the ability to acquire new skills and technologies. Outstanding spoken and written communication skills are essential
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply