56 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" research jobs at Oak Ridge National Laboratory
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array of capabilities in nuclear nonproliferation, data analytics, cybersecurity, cyber-physical resiliency, geospatial science, and high-performance computing, our organization seeks to produce world
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materials. In this role, you will develop and apply methods that integrate physics‑guided image correction with intelligent (AI/ML‑enabled) data‑acquisition strategies. Key objectives include (1) implementing
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, and adapt to ever changing needs Preferred Qualifications: Familiarity with containerization technologies and microservices Familiarity with basic machine learning and data analysis pipelines (ingestion
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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comparative research across Mojo, Julia, Rust, and vendor toolchains. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or related field. Experience with LLMs or agentic AI frameworks
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Laboratory. Major Duties/Responsibilities: Develop and implement advanced time-frequency and spectral analysis techniques for high-frequency voltage/current waveform data Apply wireless PHY-layer concepts