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Research Associate

  • ... Posted on: Mar 16, 2026
  • ... Brookhaven National Laboratory
  • ... Upton, Kentucky
  • ... Salary: Not Available
  • ... Full-time

Research Associate   

Job Title :

Research Associate

Job Type :

Full-time

Job Location :

Upton Kentucky United States

Remote :

No

Jobcon Logo Job Description :

Position Description The National Synchrotron Light Source II at Brookhaven National Laboratory seeks a highly motivated and innovative Postdoctoral Research Associate to join the Spectroscopy Program. The successful candidate will contribute to an advanced Laboratory Directed Research and Development (LDRD) project, “Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis,” aimed at revolutionizing real-time analysis of X-ray Absorption Spectroscopy (XAS) data. Working at the Inner Shell Spectroscopy (ISS) and Quick Absorption and Scattering (QAS) beamline, which provides intense hard X-rays for probing structure and reactivity across diverse materials, such as catalysts, quantum materials, energy storage systems, and superconductors, you will develop and deploy cutting‑edge AI/ML algorithms for real-time Extended X‑ray Absorption Fine Structure (EXAFS) analysis. This project is central to advancing autonomous experimental capabilities at NSLS‑II, enhancing the speed, accuracy, and impact of in‑situ and operando XAS experiments. Essential Duties and Responsibilities Develop and optimize AI/ML models (e.g., random forest, autoencoder, transformers, mixture‑of‑experts frameworks) for automated EXAFS data interpretation. Generate, curate, and augment training datasets using FEFF‑based simulations and experimental data. Conduct beamline experiments to validate model predictions and integrate them into real‑time analysis workflows as an extension to current beamline data analysis routine. Collaborate closely with beamline scientists, computational researchers, chemists and multi‑institutional users to implement ML‑assisted XAS pipelines. Present findings at national and international conferences and publish in high‑impact scientific journals. Communicate research progress, challenges, and achievements, and engage within and beyond the department to explore new potential collaborations. Required Knowledge, Skills, and Abilities Ph.D. in Physics, Materials Science, Chemistry, or a related field. Demonstrated strong background in machine learning, data analysis, and software development using Python. Proven track record of peer‑reviewed publications. Excellent communication skills and a collaborative, team‑oriented mindset. Preferred Knowledge, Skills, and Abilities Hands‑on experience performing FEFF calculations and data preprocessing for machine learning applications. Practical experience developing and training models using PyTorch, TensorFlow or scikit‑learn. Experience working in high‑performance computing environments, including data‑intensive simulations or model training. Familiarity with in‑situ and operando experimental design, particularly in synchrotron‑based spectroscopy. Experience applying machine learning methods to scientific data analysis or materials characterization problems. Proven research record involving X‑ray Absorption Spectroscopy or related structural characterization techniques, demonstrated through peer‑reviewed publications. Other Information Appointment Term: 2 years. On‑site at Brookhaven National Laboratory, Upton, NY. Candidates must have received a Ph.D. by the commencement of employment. BNL policy requires that after obtaining their Ph.D., 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. Why Join Us? This position offers an exceptional opportunity to contribute to the future of autonomous materials characterization. The project’s outcomes will directly enhance the efficiency of XAS experiments at NSLS‑II and pave the way for AI‑integrated beamline operations, impacting a broad user community spanning energy materials, catalysis, and quantum research. Compensation and Benefits Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71,900.00 - $88,000.00 per year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group. Brookhaven National Laboratory offers a comprehensive employee benefits program. For more information, see BNL | Benefits Program. Equal Opportunity Employment Brookhaven Science Associates is an Equal Employment Opportunity Employer‑Vets/Disabled. We are committed to fostering a respectful and collaborative environment. All qualified applicants are considered without regard to any characteristic protected by law. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request accommodation. *VEVRAA Federal Contractor. #J-18808-Ljbffr

View Full Description

Jobcon Logo Position Details

Posted:

Mar 16, 2026

Reference Number:

14660_3F2ECA54786766BE21805D8EB8535108

Employment:

Full-time

Salary:

Not Available

City:

Upton

Job Origin:

APPCAST_CPC

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Position Description The National Synchrotron Light Source II at Brookhaven National Laboratory seeks a highly motivated and innovative Postdoctoral Research Associate to join the Spectroscopy Program. The successful candidate will contribute to an advanced Laboratory Directed Research and Development (LDRD) project, “Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis,” aimed at revolutionizing real-time analysis of X-ray Absorption Spectroscopy (XAS) data. Working at the Inner Shell Spectroscopy (ISS) and Quick Absorption and Scattering (QAS) beamline, which provides intense hard X-rays for probing structure and reactivity across diverse materials, such as catalysts, quantum materials, energy storage systems, and superconductors, you will develop and deploy cutting‑edge AI/ML algorithms for real-time Extended X‑ray Absorption Fine Structure (EXAFS) analysis. This project is central to advancing autonomous experimental capabilities at NSLS‑II, enhancing the speed, accuracy, and impact of in‑situ and operando XAS experiments. Essential Duties and Responsibilities Develop and optimize AI/ML models (e.g., random forest, autoencoder, transformers, mixture‑of‑experts frameworks) for automated EXAFS data interpretation. Generate, curate, and augment training datasets using FEFF‑based simulations and experimental data. Conduct beamline experiments to validate model predictions and integrate them into real‑time analysis workflows as an extension to current beamline data analysis routine. Collaborate closely with beamline scientists, computational researchers, chemists and multi‑institutional users to implement ML‑assisted XAS pipelines. Present findings at national and international conferences and publish in high‑impact scientific journals. Communicate research progress, challenges, and achievements, and engage within and beyond the department to explore new potential collaborations. Required Knowledge, Skills, and Abilities Ph.D. in Physics, Materials Science, Chemistry, or a related field. Demonstrated strong background in machine learning, data analysis, and software development using Python. Proven track record of peer‑reviewed publications. Excellent communication skills and a collaborative, team‑oriented mindset. Preferred Knowledge, Skills, and Abilities Hands‑on experience performing FEFF calculations and data preprocessing for machine learning applications. Practical experience developing and training models using PyTorch, TensorFlow or scikit‑learn. Experience working in high‑performance computing environments, including data‑intensive simulations or model training. Familiarity with in‑situ and operando experimental design, particularly in synchrotron‑based spectroscopy. Experience applying machine learning methods to scientific data analysis or materials characterization problems. Proven research record involving X‑ray Absorption Spectroscopy or related structural characterization techniques, demonstrated through peer‑reviewed publications. Other Information Appointment Term: 2 years. On‑site at Brookhaven National Laboratory, Upton, NY. Candidates must have received a Ph.D. by the commencement of employment. BNL policy requires that after obtaining their Ph.D., 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. Why Join Us? This position offers an exceptional opportunity to contribute to the future of autonomous materials characterization. The project’s outcomes will directly enhance the efficiency of XAS experiments at NSLS‑II and pave the way for AI‑integrated beamline operations, impacting a broad user community spanning energy materials, catalysis, and quantum research. Compensation and Benefits Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71,900.00 - $88,000.00 per year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group. Brookhaven National Laboratory offers a comprehensive employee benefits program. For more information, see BNL | Benefits Program. Equal Opportunity Employment Brookhaven Science Associates is an Equal Employment Opportunity Employer‑Vets/Disabled. We are committed to fostering a respectful and collaborative environment. All qualified applicants are considered without regard to any characteristic protected by law. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request accommodation. *VEVRAA Federal Contractor. #J-18808-Ljbffr

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