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semantic representation models for sign language. Such representations are key to allowing SL to be efficiently processed by large language models (LLMs), and will lead to machine learning models that can
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evolution and protein optimisation, applying molecular biology and biophysics. Researchers will be supported to develop skills in the latest AI or machine learning tools for protein design. According
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inverse modeling methods, machine learning, and artificial intelligence techniques. Appointment Details: Start date: As early as February 1, 2026. Annual Salary: $52,000 Application review: Ongoing until
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applied or fundamental research and publish the results in high-quality conferences and journals; Developing Computational Intelligence (e.g., Machine Learning and Optimization models) applications and
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to conduct multidisciplinary research around robot learning for autonomous robotic chemists, with a background of excellent research outputs across Robotics and Machine Learning, ideally with a background in
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for safety-critical bilateral teleoperation. The research will leverage a combination of passivity-based control methods and machine learning techniques to enable reliable and robust teleoperation in uncertain
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of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
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functional theory) and high-performance computing. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to
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automating geospatial workflows. Proficiency with GIS tools (e.g., QGIS, ArcGIS) for spatial analysis and visualization. Experience developing statistical or machine learning models to estimate fuel moisture
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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