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Episteme, Condensed Matter Theory Group Position ID: Episteme-Condensed Matter Theory Group-POSTDOC [#31188] Position Title: Position Type: Postdoctoral Position Location: Cambridge, Massachusetts
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modelling are essential. Experience with healthcare data, algorithmic fairness, or deep learning for biomedical data will be advantageous. The successful candidate will contribute to high-impact publications
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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mathematics or a related field strong background in image processing and analysis, including deep learning (e.g., CNNs) experience with correlative imaging workflows and 2D/3D registration techniques strong
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experience level at appointment. See the following table(s) for the current salary scale(s) for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23
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or experimental research involving passive, active, specialty, or telecommunication optical fibers, or in modeling linear and nonlinear phenomena—including the use of deep learning methods—in the field of optical
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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mutual agreement. Appointment Start Date: As soon as possible Group or Departmental Website: https://med.stanford.edu/solutions.html (link is external) How to Submit Application Materials: Please submit