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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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challenging and impactful research and development programs in healthcare informatics, bioinformatics, high performance computing and deep learning. We have a collaborative environment focusing on designing
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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the following requirements: Contribute to and progressively lead Artificial Intelligence (AI) & Machine Learning (ML) engineering support on an ongoing basis as evidenced by, for example, innovative artifacts
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the ability to learn independently. Excellent verbal communication skills. Desire and ability to work collaboratively in a dynamic team environment. At least three of the following: Mechanical design
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Directorate. In this role, you will lead the development and application of physics-informed data science and machine learning approaches to support nuclear nonproliferation missions. The successful candidate
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Write software to support cutting edge research and facilitate Proof of Concept demonstrations Implement, evaluate, and enhance machine learning pipelines for cybersecurity applications Basic
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of complex systems in support of the scientific mission of the Laboratory and of the Department of Energy. The role expects collaborations with scientists in interdisciplinary research projects within the Oak
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and distribute monthly performance reports. Team Collaboration: Provide backup support to the division office and collaborate with other administrative staff as needed. Special Projects: Participate in
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seeking a Geospatial Data Engineer to support research and operational workflows focused on scalable geospatial data science, applied machine learning, and production-grade engineering practices to deliver