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Field
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%-100% effort. Qualifications All required qualifications must be documented on application materials. Required Qualifications PhD in Biomedical Eng., Computer Science/Eng., Electrical Eng., Math
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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around 15 are PhD students. The work environment is open and welcoming, striving to provide each employee with the opportunity to develop personally and professionally. The field of solid mechanics relates
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exclusion criteria apply. For more information, please visit the University of Washington Labor Relations website . Required Qualifications: Completed PhD in biomedical engineering, electrical engineering
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develop signal processing algorithms to characterize structural health in microreactors and other advanced nuclear reactor technologies. Metrics for success will include scientific output, disseminating
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control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse