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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
/or oceanography; or experience working with numerical simulations, large data, scientific programming, and/or machine learning. Applicants are asked to send a CV, a brief statement of research
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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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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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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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assets include strong programming skills, experience with modern machine-learning techniques such as neural simulation-based inference or transformer architectures, and familiarity with fitting methods and
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of Energy (DOE) experimental facilities. This role involves research and development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high
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, are considered. The participant will gain experience in multi-scale computational modeling and machine learning of mechanical behavior of high temperature alloys. They will be a part of interdisciplinary team and
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for support in technology development. You will work closely with a PhD researcher at the German partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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of reactive force field molecular simulations, supervised machine learning techniques and understanding of mass spectrometry techniques. The post is available for 3 years from 1 September 2026. If you are still