56 phd-in-computer-vision-and-machine-learning Postdoctoral positions at Oak Ridge National Laboratory
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) with questions related to this position. Major Duties/Responsibilities: Develop and apply machine learning models (ML) as surrogates for high-resolution process-based hydrologic models. Design and
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Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD
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, health, and quality program requirements. Maintain a strong commitment to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors, priorities, and
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optical systems, thermal imaging, pyrometry, spectroscopy, high speed imaging or acoustic sensing. Familiarity with data analytics, machine learning, or signal processing. Knowledge of metal additive
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scientific papers in key journals and present at key meetings. Ensure compliance with environment, safety, health, and quality program requirements. Maintain a strong commitment to the implementation and
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computing environments. Interest or experience in machine learning, inverse problems, or AI for scientific data. Strong record of research productivity and ability to work effectively in a collaborative
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in
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challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
that can incorporate multi-scale computational simulations to aid with data fusion across multiple modalities of experiments with the final goal of discovering novel materials phenomena or even new materials
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purification of electrode or electrolyte systems and evaluation of their battery performance. The program will have a strong collaborative component with characterization (e.g. electron microscopy