49 phd-data-maining-"Computer-Vision-Center" Postdoctoral positions at Oak Ridge National Laboratory
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Methods and Dynamics (MMD) Group at Oak Ridge National Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Methods for Data Reduction. Topics
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Requisition Id 15997 Overview: We are seeking a postdoctoral researcher who will focus on atomistic simulation and data science approaches. This position resides in the Chemical Transformations
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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postdoctoral research associate to advance the state of scientific AI by addressing cross-cutting challenges in data readiness for AI to enable scalable, reproducible AI workflows on leadership-class systems
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experiments to neutron reflectometry studies. The main objectives are: (1) To implement fluorescence microscopy techniques and Flicker spectroscopy to studies of DIBs under electrical stimulation; (2) Use other
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will involve designing beam dynamics experiments, measurement, simulation, and data analysis. This position resides in the Accelerator Physics Group in the Accelerator Science and Technology Section
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, United States of America [map ] Appl Deadline: (posted 2025/10/03 05:00 AM UnitedKingdomTime, listed until 2026/04/04 04:59 AM UnitedKingdomTime) Position Description: Apply Position Description Overview: The Data and AI
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interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Basic Qualifications: A PhD in in condensed matter physics, theoretical physics, quantum information, or a closely related
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characterizations. Experience with user facilities. Data analysis of structural, electronic, magnetic, and topological properties. Work with others to maintain a high level of scientific productivity. Publish
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in Computer Science or a related discipline. A strong background in scientific data