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Requisition Id 15751 Overview: The Advanced Computing in Health Sciences (ACH) section at the Oak Ridge National Laboratory is seeking qualified applicants for a Machine Learning Engineer position
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science, decision science, discrete algorithms, multiscale methods, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems
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(PMI) Science Focus Area and the GPTgp (Generative Pretrained Transformer for Genomic Photosynthesis) project. This position focuses on developing machine learning pipelines, AI-driven scientific
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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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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fabrication Machine learning (ML)/artificial intelligence (AI) coursework Experience with AI/ML libraries (TensorFlow, PyTorch) Special Requirements: Work involves various physical requirements and working
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expected to contribute to the development and application of advanced manufacturing simulations, and machine learning (ML) models relevant to additive manufacturing, virtual manufacturing, material
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, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
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informed of class logistics. Use the Learning Management System (LMS) for monitoring registrations, determining class assignments, setting delivery schedules, printing rosters, and verifying training records