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, and satellite technologies; and • Digital engineering, digital twin systems, artificial intelligence and machine learning, quantum computing, and advanced computational methods. Experience with
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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 10 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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. Experience in artificial intelligence or machine learning approaches applied to materials research will be considered a plus. We regret to inform that only shortlisted candidates will be notified. Hiring
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team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity Employer: Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard
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sciences units that support academic, clinical, and simulation-based learning environments. Act as a strategic partner to deans, department chairs, and clinical leadership to anticipate and meet technology
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to apply for a faculty or staff position using the Career worklet, please review this tip sheet . The Department of Civil and Architectural Engineering is seeking Part-Time Faculty to teach courses
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will be available to teach a required first-year legal research, analysis, and writing course and may teach upper-level legal research or technology courses. The librarian will also provide reference and
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network structures. Methods from graph theory, machine learning, and artificial intelligence will be employed to model complex relational structures and identify patterns in high-dimensional data. The work
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engineering? Then this professor position might be for you. We are looking for a new professor to lead research in probabilistic machine learning, with a focus on areas such as deep generative models, Bayesian