58 cyber-security-machine-learning Postdoctoral research jobs at Oak Ridge National Laboratory
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Signals Collections and Analysis Group in the Nuclear Nonproliferation Division
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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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Requisition Id 15885 Overview: We are seeking a Postdoctoral Research Associate – Simulation and Machine Learning for Composite Manufacturing who will focus on developing physics-based simulation
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strengths in any of these areas — quantitative imaging, modeling/transport science, machine learning, or scientific programming — are encouraged to apply. Major Duties/Responsibilities: Lead energy‑storage
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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competing structural phases and the vibrational and electronic structure in materials with defects and disorder. This effort will further seek to implement strategies to leverage machine learning techniques
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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