24 Postdoctoral Fellowship at Oak Ridge National Laboratory, United States

Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences (CNMS) Division is seeking a Postdoctoral Research Associate to join an exciting and dynamic research environment. This position sits at the intersection of spin-based quantum sensing, optical imaging, solid-state single-photon sources, and fundamental materials science. At CNMS, we leverage the unique properties of quantum systems, such as color centers in diamonds, to develop innovative sensing techniques with applications in magnetic imaging. Our spin-based quantum sensing capabilities are undergoing significant expansion, with the installation of an ambient scanning nitrogen vacancy (NV) microscope, the imminent addition of a cryogenic scanning NV microscope, and the construction of a new cryogenic widefield/confocal spin-based sensing platform. These cutting-edge platforms will enable the successful candidate to pioneer new imaging and sensing modalities, explore novel solid-state spin sensors, and investigate nanoscale magnetic order and spin fluctuations.

In addition to NV centers in diamond, emerging solid-state single-photon sources such as color centers in hexagonal boron nitride (hBN) offer exciting potential for photonic quantum information technologies. As a postdoctoral scholar, you will have the opportunity to investigate these novel quantum emitters, particularly hBN-based systems, fabricate photonic interfaces, and characterize photon and spin properties using a cryostat integrated with microwave sources and superconducting nanowire single-photon detectors. You will have the ability to focus on quantum sensing, quantum emitters, or both, allowing for flexibility based on your research interests and expertise. This position resides in the Scanning Tunneling Microscopy Group, Nanomaterials Characterization Section, CNMS Division, Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory.

The Manufacturing Energy Efficiency Research & Analysis (MEERA) Group in the Manufacturing Science Division (MSD) at Oak Ridge National Laboratory (ORNL) is seeking applicants for a postdoctoral research associate position in energy efficiency and decarbonization for the industry sector. This position augments ORNL’s industrial energy efficiency and decarbonization team, which operates in support of DOE’s Better Plants and Better Climate Challenge programs. The mission of the MEERA group is to research, analyze, and disseminate knowledge on energy, carbon, water, and material efficiency in the manufacturing sector and to develop, deploy, and promote impactful practices, tools, and technologies. The MEERA group is a part of ORNL’s Manufacturing Science Division in the Energy Science and Technology Directorate.

Through its energy efficiency & decarbonization technical assistance programs, the MEERA group develops a diverse portfolio of industrial energy efficiency tools and resources delivered to the manufacturing sector through various technical assistance and training events worldwide. The MEERA group actively supports industry partners in improving manufacturing plant energy efficiency and decarbonization through roles in the U.S. Department of Energy’s Better Plants and Better Climate Challenge programs.  

The Grid Interactive Controls (GIC) 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. The Grid Interactive Controls group specializes in pioneering innovations at the edge of today’s power grid, concentrating on fortifying grid security, enhancing reliability, bolstering resilience and advancing decarbonization. Our primary focus lies in the comprehensive ‘Everything-to-Grid’ (X2G) strategies, developing cutting-edge solutions in grid-edge integration and control. Our commitment revolves around seamlessly incorporating emerging distributed energy resources, including demand response emerging at the grid edge, providing essential services crucial to its reliable operation. Employing a diverse range of disciplines such as urban modeling, control theory, optimization, economics, game theory, data analytics, and machine learning, the GIC Group delves deeply into understanding intricate grid-edge interactions and operations. Researchers are dedicated to laying the groundwork for optimal X2G integration and utilization. Group initiatives encompass advanced urban system modeling, analysis & visualization, low-cost wireless sensing technologies, and interoperable & scalable control mechanisms tailored for the grid edge. Research promotes grid-interactive efficient buildings as a pivotal component in advancing building-to-grid integration, amplifying their role in electrification of heating and ultimately shaping the future decarbonized grid.

Specifically, the urban energy modeling team within the GIC Group has created and simulated a model of every U.S. building. This involves urban-scale building energy modeling at the resolution of individual buildings and at the scale of nations to analyze building codes, energy efficiency, demand response, and climate change impacts toward a sustainable and resilient built environment. These activities involve multi-disciplinary collaboration across ORNL, collaborative partnerships and NDAs with over 20 well-known companies, and significant awards on world-class computational resources. This team achieved world-first simulation of 125.7 million U.S. buildings, public release of 122.9 million building energy models (bit.ly/ModelAmerica), and has scaled EnergyPlus to over 1 million simulations per hour on supercomputers. In partnership with major organizations, the team is actively improving the data and algorithms of the Automatic Building Energy Modeling (AutoBEM, bit.ly/AutoBEM) software suite which involves big data processing, data analytics, machine learning, high-performance computing resources, computer vision, and building science to create, model, simulate, validate, and analyze building performance to create software prototypes (e.g. dashboards, bit.ly/virtual_epb) for actionable use of building data, models, or analysis by specific stakeholders. Over 50 million core-hours have been awarded to release a Model America v2.0 dataset in 2022.

Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general guidance, and is expected to prepare manuscripts for scientific publication and present the work to sponsors and at conferences. This position requires development of innovative software techniques, knowledge of building energy modeling, multi-sector grid edge technology integration, frequent and consistent review of related literatur. It also requires frequent interactions and collaboration with a multi-disciplinary team of researchers from universities, national laboratories, and private industry for the development of technical capabilities, demonstrations, proposals, oral presentations, and publications.

As part of the urban energy modeling team, the candidate will assist in the development and implementation of data organization and software development for scalable use and analysis of business-sensitive data by supporting senior R&D staff in 1) the invention or improvement of innovative algorithms for detection or estimation of building characteristics, 2) validation against known data sources, 3) scalable generation/simulation of buildings using OpenStudio and EnergyPlus, and/or 4) use of Artificial Intelligence (AI) techniques to quantify and improve city-to-nation scales of individual building energy models. As part of the R&D, the candidate will be required to apply the computational skills to manage big data, create and extend existing software capabilities, and develop user-centered web interfaces; and utilize the system engineering knowledge to ensure seamless integration of data, algorithms, and knowledge into comprehensive solutions.

We are seeking a Postdoctoral Research Associate who will support the Biostatistics and Biomedical Informtatics group in the Computational Sciences & Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL).

You will have a unique opportunity to work in a collaborative research and development environment focusing on biostatistics, artificial intelligence (AI) and machine learning (ML). We are specifically seeking a candidate with solid experience with handling multimodal healthcare data. We are looking for someone with innovative thinking to design and implement statistical, AI and ML algorithmic solutions to real world problems in healthcare and biomedical research.

You will have the opportunity to conduct computational research and collaborate with scientists within the group as well as with external partners which may include other national laboratories, academia, or medical centers.

You will also perform groundbreaking research on a wide range of significant problems with the fastest computing platforms in the world. This position requires novel thinking, teamwork, and discovery in finding new approaches for analyzing massive and complex data, collaborating with worldwide experts, and publishing groundbreaking results.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

We are seeking a Postdoctoral Research Associate who will focus on advanced scanning probe microscopy to study the dynamics of ferroic systems ( ferroelectric and ferroelastic materials) under different external stimuli such as electric fields, light and strain. This position resides in the Functional Atomic Force Microscopy (FAFM) group in the Nanomaterials Characterization Section, Center for Nanophase Materials Sciences (CNMS), Physical Science Directorate (PSD) at Oak Ridge National Laboratory (ORNL).  

As part of our research team, you will investigate the functional properties of ferroic systems integrated in heterostructures and devices for microelectronic applications, their characteristic topological configurations, e.g., domains and domain walls, and how they dynamically behave under light, electrical, or strain stimuli. You will utilize ORNL’s unique capabilities of ultra-high vacuum, glovebox, and ambient atomic force microscopy in conjuction with the extensive toolbox of internally developed modalities to further understand environmental and temperature dependent functional properties. You will have the unique opportunity to develop cutting-edge scanning probe microscopy techniques targeted at discovering underlying new phenomena. In this regard, a particular topic of interest will be the dynamics of topological structures such as ferroelectric and ferroelastic domain walls as a function of their complex nature to better understand how to use them as single active elements and their impact when integrated in nanodevices.

Another focus of the research will be to understand how a new class of ferroelectrics, including wurtzite and fluorite structures, behave on the nanoscale through the development of new techniques and mulitdimensional data analysis. Here, understanding structure-property realationships of this new class of ferroelectrics will directly aid in the development of technologies vital to logic and computing applications. You will play an integral roll in atomic force micrscopy and closely collaborate with other scientists for synthesis, device fabrication, theoretical calculations, and other characterization methods, across multiple CNMS groups and divisions at ORNL and collaborate directly with the Energy Frontier Research Center team at Pennsylvania State University. 

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 advised by Melissa Cregger who will support the Integrative Microbiomics Group in the Biosciences Division, Biological and Environmental System Sciences Directorate at Oak Ridge National Laboratory (ORNL). The Post doctoral Associate will collaborate with a group of scientists to examine how variation in plant-microbe associations influences host physiology and ecosystem carbon cycling.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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 Thermal Energy Storage Group in the Buildings and Transportation Science Division (BTSD), Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) is seeking qualified candidates to fill the Postdoctoral Research Associate position. The work in this group supports the U.S. DOE Building Technology Office, Geothermal Technology Office, and other customers by developing state-of-the-art building equipment for energy efficiency, equipment-to-grid integration, and improved life cycle climate performance.

We are seeking a Postdoctoral Research Associate who will support the Computational and Predictive Biology Group in the Biosciences Division (BSD), Biological and Environmental Systems Sciences (BESSD) at Oak Ridge National Laboratory (ORNL).  

The Biosciences Division is focused on advancing science and technology to better understand complex biological systems and their relationship with the environment. BSD has expertise and special facilities in genomics, computational systems biology, microbiology, microbial ecology, biophysics, and structural biology. Computational systems biology research includes methods development and use to analyze large scale omics, greenhouse, field, and clinical datasets to derive insights and hypotheses suitable for further experimental validation and to improve researchers’ ability to further advance understanding of biological systems.

We develop and apply computational methods to explore biological processes at all levels of life systems organization from atomistic to ecological scales. The collection of omics, phenotyping and environmental data, and automation of its analysis and discovery, is becoming increasingly important as the scale of experiments grow and diversify for projects at ORNL including the Center for Bioenergy Innovation, Plant Microbe Interfaces, Secure Ecosystem Engineering and Design, Integrated Pennycress Resilience projects, funded by the DOE, and Biomedical projects, funded by the NIH and VA, and pandemic prevention projects funded by the NSF and other government agencies, among other efforts that also include access to suitable large-scale computational resources.

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 support the Advanced Computing for Chemistry & Materials in the National Center for Computational Sciences (NCCS), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) to perform leading-edge computational chemistry research and development for molecular electronic structure and applications in catalysis, 3d metal chemistry, electronic properties. This role will involve performing large-scale simulations using high performance computing (HPC) resources of Oak Ridge Leadership Facility. Coding in common HPC programming languages and GPU programming are desirable. Close collaborations are expected with researchers from across ORNL with expertise in chemical separations, materials, and spectroscopy. The successful candidate will be mentored and teamed with staff in the National Center for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically targeted at the key DOE Office of Science missions. 

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

We are seeking a Postdoctoral Research Associate who will focus on developing uniform, reproducible, and controlled large-scale synthesis and transfer of 2D materials, primarily transition metal dichalcogenides and various forms of boron nitrides. Our team uses bottom-up synthesis techniques, including CVD, MOCVD, and PECVD, coupled with multiple characterization techniques to control the growth environment and material consistency across the wafer targeting applications in microelectronics and quantum information science. This position resides in the Functional Hybrid Nanomaterials (FHN) Group in the Center for Nanophase Materials Sciences (CNMS), Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL).

As a postdoc, you will work with a research team at the CNMS primarily focused on wafer scale synthesis and transfer, emphasizing reproducible and uniform growth of 2D materials, managing 2D interface structure and contamination, and developing desired property engineering on a large scale. Growth methods include traditional approaches such as CVD, PECVD, and MOCVD. Developing novel roll-to-roll (R2R) 2D synthesis methods, including innovative precursor and energy delivery systems relying on novel precursor chemistries, growth regimes that yield uniform and consistent growth, and allowing reliable material doping schemes will be stressed. The envisioned development of novel transfer approaches includes investigating new 2D material handling techniques and employing innovative support matrices and processes that yield clean 2D interfaces and controls wrinkle formation. You will also work with the project team to set up and automate CVD systems and transfer stations with real-time adaptive control. The novel materials synthesized in this project will be collaboratively shared with various scientists and engineers, including electron microscopists, ultrafast spectroscopists, device fabrication experts, and quantum information scientists, to explore their functionalities across a broad spectrum of capabilities developed by ORNL.

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. With a dedicated and creative staff of over 6,000 people, ORNL’s decadal vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

We are seeking a Postdoctoral Research Associate with expertise in artificial intelligence (AI) and machine learning (ML) for multiscale physical systems. This position resides 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.

The selected candidate will join the Multiscale Materials (MsM) group within the Advanced Computing Methods for Physical Sciences Section in CSED. The MsM group is dedicated to delivering multiscale, multi-fidelity computational models, systems, and AI/ML tools using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. In this role, the postdoctoral researcher will focus on developing trustworthy foundation models for fluid dynamics and turbulent flows. This will involve designing efficient and trustworthy ML algorithms for physical systems, scalable data loading and training methods for exascale computing platforms, and model verification and validation. The position offers an excellent opportunity to collaborate with multi-disciplinary domain scientists and advance large-scale scientific AI/ML models.       

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

We are seeking a Postdoctoral Research Associate who will support the Computational Urban Sciences Group in the Computational Sciences and Engineering Division (CSED), Computing and Computational Sciences (CCSD) at Oak Ridge National Laboratory (ORNL). The postdoc will focus on applications of Artificial Intelligence (AI), Machine Learning (ML), and Operations Research on Urban Systems. The role is expected to use data-driven approaches to develop and foster novel scientific research in the areas of building energy, electric grid and energy systems, transportation systems, natural hazards, and their impact on urban systems, as well as response to other non-natural emergencies. The ideal candidate is expected to bring expertise in the application of AI, ML, anomaly detection, network science, urban health and modeling and simulation. Prior experience of applying such knowledge to the understanding of urban systems is preferred.

The Computational Urban Sciences Group is comprised of a multi-disciplinary team of scientists carrying out applied research at the intersection of computing and complex urban systems in the emerging environment of smart cities, energy infrastructures, infrastructure siting, smart grid, smarter and sustainable mobility, responsive buildings, extreme and persistent weather, climate science, and data driven emergency response and resiliency. The advances are enabled by the growing body of technologies that includes big-data, ML, high-performance computing, cloud computing, graph analytics, visual analytics, modeling and simulation, and visualization. The candidate must be comfortable working as part of a tightly integrated team and must be capable of supporting multiple projects simultaneously.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

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).

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

We are seeking a Human-Centered Design Postdoctoral Research Associate who will focus on quantifying and improving human interaction with manufacturing systems and digital aids for manufacturing processes.  This position resides in the Manufacturing Systems Design Group in the Manufacturing Sciences Division of the Energy Science and Technology Directorate at Oak Ridge National Laboratory (ORNL).  

As part of our research team, you will quantify the current complexity of interactions and information flow, to inform the design of next generation interfacing between human, manufacturing systems, and digital tools. It is critical to understand the sensing and metrics needed to enable better CAM workflows, operator strategies and redesign efforts for the newest convergent manufacturing systems. This work will ultimately result in exploration of Human-AI interactions for both operators and designers in manufacturing contexts.

We are seeking a Postdoc who will focus on microstructural characterizations of nuclear ceramics and mechanistic modeling of the material degradation behavior under nuclear reactor relevant environments. This position resides in the Nuclear Energy Materials Microanalysis in the Materials in Extremes section, MSTD, PSD, at Oak Ridge National Laboratory (ORNL).  

The Postdoctoral Research Associate will contribute to the development of novel modeling and characterization frameworks that will be based on 1) simulation or characterization of the microstructures of ceramics using 3D characterization techniques, 2) establishing connections between material structure and mechanical properties, 3) predicting the behavior of ceramics under extreme environments. Moreover, the candidate will contribute to the constitutive modeling frameworks and develop image-based models for high-temperature ceramics. Knowledge and experience of relevant characterization techniques, including x-ray computed tomography, scanning electron microscopy, or other microscopy 3D techniques, is desirable. These modeling and microscopy approaches will be combined with experimental data to evaluate various ceramic materials. Demonstrated experience in implementing nonlinear constitutive models in commercial finite element (FE) codes is desirable. You will be expected to collaborate with research staff and industry partners focused on material research and development through computational modeling and multimodal characterization.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

We are seeking a Postdoctoral Research Associate who will focus on developing and applying machine learning algorithms relevant to autonomous experimental laboratories. This position resides in the Data NanoAnalytics (DNA) group in the Theory and Computation section, Center for Nanophase Materials Sciences, Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL).  

In this role, you will work as part of an interdisciplinary team from Oak Ridge National Laboratory and partner Universities to develop algorithms for human-in-the-loop autonomous experimental workflows. You will also work closely with CNMS staff to implement these algorithms on automated instruments such as scanning probe and/or scanning transmission electron microscopes, and gain experience in setting up and using data and analysis pipelines.

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 focus on the development and/or application of density functional theory (DFT) as well as correlated electronics structure methods such as quantum Monte Carlo (QMC), GW/BSE, dynamical mean field theory (DMFT), among others, for strongly correlated topological quantum materials. The position resides in the Nanomaterials Theory Institute (NTI) at the Center for Nanophase Materials Sciences Division (CNMS), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL) and will be associated with the Heterogeneities in Quantum Materials (HQM) theme science research at the CNMS.

As a Postdoctoral Research Associate, you will contribute to research by bridging state-of-the-art atomistic simulation methods with nanoscale experiments and domain-informed AI/ML algorithms. In addition to fundamental science discovery, the research will pursue the development of automated computational workflows for multi-fidelity modeling and simulation as well as development of ML-approaches that allow efficient integration of different theory and simulation tools with automated experimental platforms. You will work closely with a team of scientists at CNMS who are experts in developing/applying different theoretical approaches as well as developing novel ML-approaches for automation of nanoscale experimental probes, such as scanning tunneling microscopy (STM) and scanning transmission electron microscopy (STEM)..

We are seeking a Postdoctoral Research Associate who will focus on Advanced electron microscopy research for quantum materials.  This position resides in the Scanning Transmission Electron Microscopy (STEM) group in the Nanomaterials Characterization Section, Center for Nanophase Materials Sciences (CNMS), Physical Science Directorate (PSD) at Oak Ridge National Laboratory (ORNL).  

As part of our team, you will investigate the atomic and electronic structures of energy and quantum materials and correlate these structures with relevant propertiesusing ORNL’s suite of aberration-corrected STEMs. A particular focus of your research will be understanding heterogeneities, such as interfaces, defects, and boundaries in quantum materials.  Advanced electron microscopy capabilities, such as 4D-STEM and high-resolution electron energy loss spectroscopy (EELS), will be integrated with in situ specimen biasing/cooling experiments. You will play an integral role in electron microscopy studies and will closely collaborate with other scientists for synthesis, theoretical calculations, and other characterization methods, across multiple divisions at ORNL. 

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 Post Doctoral Research Associate to perform R&D in the areas of EMT simulation and software development as well as dynamic and transient inverter modeling. Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general guidance, and is 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.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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 Computational Hydrology and Atmospheric Science Group (CHAS) at the Oak Ridge National Laboratory (ORNL) is seeking a qualified postdoctoral candidate in the fields of Hydrological and Earth System Modeling and Artificial Intelligence (AI) with a strong background in computational sciences, statistics, hydrological modeling, and Earth system modeling. ORNL’s CHAS group conducts world-class research and development in hydrological and Earth system modeling, large scale data analytics and machine learning (ML), and model-data integration at the US Department of Energy’s (DOE’s) Leadership Class Computing Facilities (LCFs).

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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. We are seeking a Postdoctoral Research Associate who will reside in the Materials Engineering Group in the Neutron Scattering Division (NSD), Neutron Sciences Directorate (NScD) at Oak Ridge National Laboratory (ORNL).

This project will be focusing on the development of advanced Artificial Intelligence (AI)/Machine Learning (ML) tools for the measurements of 3D tensorial strain in crystalline materials using neutrons at the Spallation Neutron Source VENUS beamline (https://neutrons.ornl.gov/venus). VENUS is nearing completion of its construction and will start commissioning in July 2024. One of the unique time-of-flight imaging capabilities enabled at VENUS is Bragg edge radiography. The measurement of the Bragg edge shift provides information of a lattice plane shift through a sample. This project aims at enabling the 3D reconstruction of the tensorial strain values in 3D using Bragg edge tomography.

Utilizing an advanced neutron imaging technique, neutron grating interferometry (nGI), to study nano-sized features in bulk materials at MARS (https://neutrons.ornl.gov/mars). By participating and contributing to this project, you will gain experience and knowledge in neutron imaging instrumentation and apply these in advancing nGI for material science research through novel instrumentation and computational methods. Then you will be applying nGI in addressing critical scientific questions in material science research. In this project, you will also have the opportunity to access other world class neutron scattering capabilities that would benefit this project and your own growth.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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 Manufacturing Energy Efficiency Research & Analysis (MEERA) Group, housed within the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at the Oak Ridge National Laboratory (ORNL) is currently seeking to fill a position for a Postdoctoral Research Associate. The role entails contributing to MEERA group’s mission of disseminating knowledge on energy, carbon, water, and material efficiency in the manufacturing sector and develop, deploy, and promote impactful practices, tools, and technologies. The ideal candidate should have a strong background in mechanical engineering, industrial energy systems, renewable energy, decarbonization, or other related fields. The candidate will play a crucial role in the planning, execution, and optimization of our technical assistance program for energy intensive industries (iron & steel, food, pulp & paper, chemicals, nonferrous metals, and nonmetallic minerals). The primary objective of the energy intensive industries (EIIs) program is to engage with manufacturers from energy-intensive industrial sectors to better understand their specific needs and issues in implementing energy efficiency and decarbonization activities. The candidate will work closely with program allies, subject matter experts and technical trade associations to ensure successful delivery of technical assistance to energy intensive manufacturing participants.

The MEERA Group actively contributes to the efforts of the Department of Energy’s Industrial Efficiency & Decarbonization Office (IEDO) by providing technical assistance. This role supports the IEDO’s vision of driving energy savings and decarbonization that can have broader impact across the energy intensive industries, which leads to cost savings, greater resilience, a strengthened workforce, and increased global competitiveness.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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 Manufacturing Energy Efficiency Research & Analysis (MEERA) Group at ORNL is seeking a Postdoctoral Research Associate to engage in research and technical support for industrial decarbonization workforce development. The ideal candidate should have a strong background in mechanical engineering, industrial energy systems, renewable energy, decarbonization, or other related fields. They should also possess experience in industrial workforce development and technical training.

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! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. 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 Grid Interactive Controls Research Group (GICR) 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. The Grid Interactive Controls group specializes in pioneering innovations at the edge of today’s power grid, concentrating on fortifying grid security, enhancing reliability, growing resilience and advancing decarbonization. Our primary focus lies in the comprehensive ‘Everything-to-Grid’ (X2G) strategies, developing cutting-edge solutions in grid-edge integration and control. Our commitment revolves around seamlessly incorporating emerging distributed energy resources, including demand response emerging at the grid edge, providing essential services crucial to its reliable operation. Employing a diverse range of disciplines such as control theory, optimization, economics, game theory, data analytics, and machine learning, the Grid Interactive Controls group delves deeply into understanding intricate grid-edge operations. Researchers are dedicated to laying the groundwork for optimal X2G integration and utilization. Group initiatives encompass innovative sensor technologies, advanced modeling techniques, and precise control mechanisms specifically designed for the grid edge. Research promotes grid-interactive efficient buildings as pivotal components in advancing building-to-grid integration, amplifying their role in electrification of heating and ultimately shaping the future decarbonized grid.

Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general guidance, and is expected to prepare manuscripts for scientific publication and present the work to sponsors and at conferences. The candidate should demonstrate theoretical and practical knowledge in control and optimization, and strong power systems domain knowledge and have experience developing software tools.

As part of our research team, the candidate will be responsible for conducting, coordinating, and reporting complex research assignments related to X2G integration, specifically: 1) Distributed Energy Resource (DER) system modeling, simulation, and analysis; 2) DER system security and privacy; 3) Grid-edge sensing, communication and control; and 4) software coding, hardware-in-the-loop simulation and hardware deployment. The candidate will also interact and collaborate with researchers from universities, national laboratories, and private industry.