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Information Number of Vacancies 1 Desired Start Date 12/01/2025 Open Date 11/11/2025 Review Start Date Open Until Filled Yes Special Instructions to Applicants To apply applicants should go to https
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related experimental data. This position resides in the Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL) and is embedded in the MAIQMag (Multimodal AI
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Executive Order No. 81 . Benefits Information A summary of benefits associated with this title/rank can be found at https://hr.uw.edu/benefits/benefits-orientation/benefit-summary-pdfs/ . Appointees solely
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physiologists, and data scientists to tackle fundamental issues in AI/ML-based photosynthesis research and applications. The selected scientist will have access to the world’s most advanced resources in computing
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on research while maintaining excellence in teaching. For more information about the Department visit: https://www.unf.edu/coas/biology/index.html . Statement(s) of Understanding This position requires a
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complete, sign, and upload the required Authorization of Information Release to your application. Reference requirements 3-5 required (contact information only) Apply link: https://aprecruit.ucmerced.edu
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of Research Authorization to Release Information Form - As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within
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information, disability, or veteran status consistent with UW Executive Order No. 81 . Benefits Information A summary of benefits associated with this title/rank can be found at https://hr.uw.edu/benefits
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, application components, or other program-related information, visit https://www.orau.gov/doe-fes-postdoc/default.html. All documents must be in English or include an official English translation. Documents sent
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models) · Histology, immunofluorescence, and biomarker quantification · Translational science platforms including organ-on-chip, bioreactor systems, and bioinformatics workflows for high-dimensional data