As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL).

The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data.  As a postdoctoral fellow at ORNL, you will collaborate with a dynamic team of scientists and engineers, leveraging cutting-edge resources; most notably the Frontier supercomputer, the world’s first exascale computing system. This is a unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum.

In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and workflows to enable AI-readiness at scale. You will work on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating with world-class scientists, you will enhance your expertise in resource optimization, scalable computing techniques, fault resilience, and advanced AI applications. This role offers unparalleled access to ORNL’s world-leading computational resources, including the Frontier supercomputer, and the chance to make meaningful contributions to DOE’s mission-critical scientific domains.

We are seeking a Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division, Computing and Computational Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency and reliability of scientific discovery. It also offers exciting prospects for direct collaboration with domain experts—such as those in neutron scattering and urban science—to apply and evaluate research methods on large, domain-specific scientific datasets.

Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.

We are seeking a Postdoctoral Research Associate who will aid the research staff in understanding the synergistic effects of various degradation phenomena of nuclear reactor fuel cladding and core internal materials. Strong materials characterization skills are required. This position resides in the Fuel Cladding and Core Internals (FCCI) Group in the Nuclear Energy and Fuel Cycle Division, Fusion and Fission Energy and Science Directorate at Oak Ridge National Laboratory (ORNL).  

The FCCI Group applies modern materials science to design, develop, optimize, and test advanced materials that will accelerate the deployment of higher performance nuclear energy systems. As part of our research team, you will evaluate accelerated testing methods (in-situ deformation + irradiation and/or corrosion) that affect the performance of structural materials deployed in extreme operating conditions and develop advanced characterization techniques to achieve these goals. You will also assess the viability of accelerated irradiation methodologies (either using ions or research reactor irradiation data) for establishing performance envelopes for materials to be deployed in advanced reactors. Efforts would in-part utilize the instrumentation and expertise available through the Low Activation Materials Development and Analysis Laboratory (LAMDA). The selected individual will be encouraged to engage with staff within the FCCI group, Nuclear Fuel Development section and across the laboratory to foster a vibrant research atmosphere to grow capabilities and drive innovation.

Metrics for success will include scientific output, disseminating results at national and international conferences and other technical meetings, and delivering on programmatic milestones.

We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel tensor network algorithms and their combination with quantum embedding approaches, with a particular emphasis on methods tailored to study nonequilibrium quantum many-body systems. These algorithms will be applied to investigate the physics of correlated quantum materials driven far from equilibrium, enabling discoveries into phenomena such as entanglement evolution, transient states and dynamical phase transitions in quantum spin and itinerant electron systems. The position will involve a combination of algorithmic innovation, numerical implementation, and collaboration with theoretical and experimental research groups. There is significant potential for high-impact research contributions at the forefront of computational quantum many-body physics.

This position resides within the Computational Chemistry and Nanomaterials Sciences group in the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL). CSED focuses on transdisciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes.

We are seeking a Postdoctoral Research Associate who will support the Accelerator Physics Group in the Research Accelerator Division, Research Accelerator Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL).

The qualified candidate will study, simulate and develop software for beam transport and beam dynamics in SNS superconducting linac, beam transfer lines and SNS Ring. The qualified candidate will also design software to monitor and control the SNS accelerator in real time and work in SNS Control Room.

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 people! These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

The Analytics and AI at Scale (AAIMS) group under Advanced Technology Section (ATS) of NCCS is hiring two postdoctoral research associates to push the frontier of agentic AI for science, scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models, in the context of leadership scientific workflows and applications. You’ll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate scientific discovery across domains (materials, chemistry, climate, fusion, biology, and more).

NCCS operates the Frontier exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you unmatched resources to prototype new ideas, run large ablations, and translate methods into scientific impact. We are an inclusive dynamic environment that welcomes those with initiative and creativity.

The Power System Resilience (PSR) Group in the Electrification and Energy Infrastructure Division (EEID) within the Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to perform R&D in the areas of electromagnetic transient (EMT) simulation and software development as well as dynamic and transient inverter modeling and different applications of the simulation. Selection will be based on qualifications, relevant experience, skills, and education. You should be highly self-motivated and independent in conducting research under general guidance and are expected to prepare manuscripts for scientific publication and present the work to sponsors and at conferences.

The PSR Group supports the research on energy security and resilience of the power grid at the Energy Department (DOE) through advancement of modeling, simulation, and real-time monitoring of the power grid, including research supporting the Office of Electricity (OE), Grid Deployment Office (GDO), Office of Cybersecurity, Energy Security and Emergency Response (CESER), and Office of Energy Efficiency and Renewable Energy (EERE) on the integration of new technologies, identifying and validating new ways of using existing and emerging grid assets to ensure grid reliability, grid resilience, environmental stewardship, and affordability of energy supplies. The PSR group focuses on resilience, data analytics, protection, and EMT simulation research.

We are seeking a highly motivated Postdoctoral Research Associate to develop advanced optical spectroscopy capabilities—including atomic-resolution electroluminescence (EL), tip-enhanced photoluminescence (PL), and tip-enhanced Raman spectroscopy (TERS)—integrated with multi-probe scanning tunneling microscopy (STM) platforms. This position resides in the Scanning Tunneling Microscopy Group in the Nanomaterials Characterization Section of the Center for Nanophase Materials Sciences Division in the Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL).  

The Postdoctoral Research Associate will focus on the development of novel multimodal optical spectroscopy methods and their integration with existing STM platforms. These capabilities will enable atomic-scale imaging and spectroscopy of structural, electronic, and optoelectronic properties in low-dimensional materials and their heterogeneities.

This position offers an exceptional opportunity to conduct research at the intersection of advanced scanning probe microscopy, solid-state single-photon emitters, nanoscale optoelectronics, and fundamental materials science. As a member of our team, the successful candidate will investigate emerging solid-state single-photon emitters and explore the optoelectronic properties of quantum and low-dimensional materials, contributing to both fundamental discovery and the advancement of next-generation technologies.

Do you have a passion for applying artificial intelligence (AI) methods for accelerating scientific discoveries and an ability to think outside of the box in a collaborative and open environment? If so, the Oak Ridge National Laboratory’s Learning Systems Group within the Data and Artificial Intelligence Systems section invites you to apply to our new postdoctoral research associate position in AI for science.

The Learning Systems Group seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will develop cutting-edge differential privacy techniques for large-scale models across multiple institutions. This position offers a unique opportunity to work with the world’s first exascale system, 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 solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing efficient techniques that maintain robust privacy guarantees while minimizing performance impact. Additionally, you will optimize the balance between privacy and utility, addressing the challenges of heterogeneous privacy budgets and varying requirements across diverse clients.

You will use Frontier’s computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also collaborate with ORNL’s AI initiative to advance secure, trustworthy, and efficient AI for science. This position offers a unique opportunity to make significant theoretical and applied contributions to differential privacy in federated learning, driving advancements in secure, collaborative AI systems globally.

As a postdoctoral researcher, you will help solve some of the most challenging problems faced by the nation. You will perform groundbreaking research on a wide range of significant problems, and you will apply your work to exciting research in multi-disciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and machine learning skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, while working with the world’s fastest computers, and disseminate innovative results through publications and presentations.

The Learning Systems Group at the Oak Ridge National Laboratory focuses on artificial intelligence and computational research and applies this knowledge to support the nation’s leading initiatives. We hire top researchers who are ready to tackle the hardest problems faced by both the US and the world. Researchers of the Learning Systems group are changing the world with their research, and we are committed to hiring and retaining highly motivated, energetic, and creative individuals that will help us continue our breakthrough scientific endeavors.

We are seeking a Postdoctoral Research Associate who will support the Manufacturing Energy Efficiency Research & Analysis (MEERA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) to work in the areas of life cycle energy impacts analysis, technoeconomic analysis, and industrial energy efficiency analysis research under the Strategic Analysis and Industrial Energy Efficiency Programs.

The MEERA Group conducts techno-economic, value chain, trade, patent, and global analyses relevant to advanced energy and manufacturing technologies. MEERA is currently supporting a multi-laboratory DOE Geothermal Technologies Office (GTO) project to develop an independent, objective, and publicly available geothermal well life cycle assessment analysis. This project will conduct research into alternative geothermal well designs that can improve the life cycle value of geothermal wells, reduce costs, improve productivity, and mitigate risks. The project builds upon previous MEERA work focusing on casing and cementing activities that identified the cost of casing, cement and cement additives, and annulus area as key variables in reducing total drilling cost. This project expands the analysis to other aspects of geothermal well development including well completion, production, and abandonment phases.

Oak Ridge National Laboratory (ORNL) (https://www.ornl.gov/) is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver solutions to compelling problems in energy and security. The Biosciences Division of ORNL (https://www.ornl.gov/bsd) has an opening for a postdoctoral researcher to conduct basic research on plant genes and phenotypes that are foundational to developing sustainable biomass feedstocks. You will join a team of diverse, inter-disciplinary scientific and technical staff working to characterize and understand the variation in plant phenotypic traits and response to stresses and link these to genetic information under the Center for Bioenergy Innovation project (https://cbi.ornl.gov/).

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop and apply scalable artificial intelligence (AI) / deep learning (DL) methods to advance multi-scale coupled physics simulations in support of the missions and programs of the US Department of Energy (DOE). ORNL’s CCP conducts world-class research and development in multi-scale computational coupled physics, large scale data analytics and DL, and model-data integration at the DOE’s leadership class Computing Facilities (LCFs). The successful candidate will demonstrate strong expertise and skills in computational materials, data analytics, development of surrogate and generative DL models, high-performance computing (HPC), and computational sciences.

We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and reactions, as well as nuclear data. The position is part of the nuclear physics team that resides in the Advanced Computing for Nuclear, Particle, and Astrophysics group at the National Center for Computational Sciences, Computing and Computational Sciences Directorate at Oak Ridge National Laboratory (ORNL). This position offers an exciting opportunity to contribute to research in nuclear theory using advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms for simulating atomic nuclei, as well as preparing data and using machine learning models for investigating how the properties of atomic nuclei connect to fundamental questions in physics, such as constraining nuclear forces, determining the limits of nuclear stability, and identifying signatures of new physics beyond the Standard Model.