Postdoctoral Research Associate

Postdoctoral Researcher

The Energy & Photon Sciences Directorate at Brookhaven National Laboratory advances forefront research in materials, chemistry, energy science, and condensed matter physics using world-class experimental and computational capabilities. As part of this directorate, the National Synchrotron Light Source II (NSLS-II) is a premier DOE Office of Science user facility that provides ultra-bright synchrotron X-rays for interdisciplinary research in physics, chemistry, biology, environmental science, and advanced materials.

NSLS-II supports thousands of users annually by enabling cutting-edge imaging, spectroscopy, scattering, and microscopy experiments across a broad range of scientific applications.

The postdoctoral researcher will develop and apply high-precision advanced manufacturing, multimodal synchrotron x-ray characterization, physics-based modeling, and AI-driven data analysis to accelerate the discovery and optimization of hierarchical metamaterials. The position involves conducting in situ synchrotron experiments at NSLS-II, integrating multimodal datasets, and developing predictive process–structure–property frameworks and closed-loop AI–experiment workflows for high-precision advanced manufacturing and materials discovery. The successful candidate will work in an interdisciplinary environment spanning high-precision advanced manufacturing, advanced characterization, and AI while contributing to DOE-aligned research programs in energy and advanced manufacturing technologies.

Essential Duties and Responsibilities:

• Conduct high-precision advanced manufacturing experiments and multimodal in situ synchrotron x-ray characterization at NSLS-II to investigate process–structure–property relationships in hierarchical metamaterials.
• Develop and apply AI-driven data analysis workflows, including multimodal data integration, image segmentation, predictive modeling, and uncertainty-aware active learning approaches.
• Perform data analysis and collaborate on physics-based simulations to support closed-loop experiment–simulation–AI frameworks for accelerated materials discovery and optimization.
• Publish research findings in peer-reviewed journals, present results at scientific conferences, and contribute to DOE-supported advanced manufacturing and AI research initiatives.

Required Knowledge, Skills, and Abilities:

• Ph.D. in materials science, mechanical engineering, physics, chemistry, data science, or a related discipline.
• Knowledge of data analysis, scientific programming, or AI/ML methods using languages such as Python, MATLAB, or C/C++.
• Experience or strong interest in high-precision advanced manufacturing, synchrotron x-ray characterization, materials processing, or advanced functional materials.
• Demonstrated ability to work independently and collaboratively in a multidisciplinary research environment.

Preferred Knowledge, Skills, and Abilities:

• Experience with synchrotron techniques such as x-ray imaging, scattering, spectroscopy, or related characterization methods.
• Familiarity with machine learning, multimodal data integration, or scientific workflow automation.

Other Information:

• Initial 2-year term appointment subject to renewal contingent on performance and funding.
• Candidates must have received a Ph.D. by the commencement of employment.
• BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness, or other life-changing events.
• This is a fully onsite position located at BNL in Upton, NY.

Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $74,000.00 - $88,000.00 / year. Salary offers will be commensurate with the final candidate's qualification, education and experience and considered with the internal peer group.