146 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" uni jobs at Oak Ridge National Laboratory
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never stop learning. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by
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in urban-scale building energy modeling, software development (esp. Python), or Artificial Intelligence/Machine Learning (AI/ML) Strong ideation, writing, and communication skills for establishing
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analysis, as well as propose and collaboratively develop new avenues of application for these techniques. Other areas of focus include applications of machine learning and artificial intelligence tools
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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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modeling, multiscale approaches) to support materials development and manufacturing process understanding. Use AI, machine learning, and data-driven methods as enabling tools to accelerate experimentation
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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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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
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and apply basic GD&T concepts. Experience with ASME piping codes and process piping system design. Experience troubleshooting mechanical or HVAC systems. Understanding of machining and fabrication
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technical leadership in AI security evaluation mechanisms. Required Qualifications Master’s Degree in Computer Science, Computer Engineering, Cybersecurity, or related fields with 7-10 years of experience
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. Experience with machine learning and data-driven approaches to diagnostic signal processing and real-time control. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL