Postdoctoral Research Associate in Total Scattering and Machine LearningJob ID 1970 Date posted 12/23/2019
Brookhaven National Laboratory is a multipurpose research institution funded primarily by the U.S. Department of Energy’s Office of Science. Located on the center of Long Island, New York, Brookhaven Lab brings world-class facilities and expertise to the most exciting and important questions in basic and applied science—from the birth of our universe to the sustainable energy technology of tomorrow. We operate cutting-edge large-scale facilities for studies in physics, chemistry, biology, medicine, applied science, and a wide range of advanced technologies. The Laboratory's almost 3,000 scientists, engineers, and support staff are joined each year by more than 4,000 visiting researchers from around the world. Our award-winning history, including seven Nobel Prizes, stretches back to 1947, and we continue to unravel mysteries from the nanoscale to the cosmic scale, and everything in between. Brookhaven is operated and managed by Brookhaven Science Associates, which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a nonprofit applied science and technology organization.
At BNL, the Energy & Photon Sciences (EPS) Directorate is working to solve grand challenges in energy that will create solutions and security for the nation’s energy system. Advances in basic science are the underpinning of transformational discoveries that rely on Brookhaven’s data-driven research, cutting-edge synchrotron science, and leadership in energy science through real-time study of working conditions in applicable energy materials. As part of the capabilities and science focus of the EPS, the National Synchrotron Light Source II (NSLS-II) is a state-of-the-art 3 GeV electron storage ring. The facility offers scientific and industrial researchers an array of instruments (beamlines) using x-ray, ultraviolet, and infrared light to enable discoveries in clean and affordable energy, high-temperature superconductivity, molecular electronics, and more.
The speed of modern synchrotron data collection has outpaced typical data analysis methods for years. This is particularly true for operando measurements, for example, in the field of heterogenous catalysis where structure-property relationships under reactive/in use conditions are critical for new technological advancements.
The goal of this project is to develop a suite of tools to aid in the measurement and prompt analysis of data from NSLS-II via machine learning methods. These tools will be commissioned on in-situ powder diffraction measurements of catalytic nanomaterials under their reactive, deteriorative, and regenerative environmental conditions. The resulting suite of tools will be deployed broadly around the facility, greatly impacting the way current and future users of synchrotron light sources approach their science.
This project spans subject matter areas from material science to data analysis and scientific computing. The successful candidate will work closely with both the X-ray Powder Diffraction beamline teams (XPD/PDF) and the Scientific Computing & Data Acquisition, Management, Analysis Group (DAMA) at NSLS-II to develop the methods.
This position is an excellent opportunity to develop expertise in both X-ray scattering and scientific computing, and the successful candidate is not required to already be experienced in both, only willing to learn.
Essential Duties and Responsibilities:
- Spearhead a focused effort to develop machine learning and AI methods for total scattering studies of energy materials.
- Develop machine learning and AI methods that will be integrated with the Bluesky data acquisition framework at NSLS-II.
- Collaborate with a wide range of researchers across a variety of disciplines including energy storage, catalysis, geology, complex oxides, quantum materials, and machine learning and AI methods both within BNL and externally.
- Publish and presents the results of these studies to the community.
Required Knowledge, Skills, and Abilities:
- PhD degree in the Physical Sciences, Material Science, Applied Mathematics, Computer Science or related field.
- Experience with neutron or X-ray powder diffraction, XAFS, imaging, or a related technique.
- Demonstrated record of scientific excellence through publications and talks.
- Ability to work collaboratively with a diverse, discipline spanning team of scientists and engineers.
Preferred Knowledge, Skills, and Abilities:
Experience in one or more of the following:
- Experience creating data analysis methods and procedures.
- Demonstrated record in collaborative software development, especially in distributed teams.
- Experience in data acquisition and analysis at a synchrotron light source, neutron source or other major scientific user facility.
- Experience with Python.
- Experience with material science, solid-state chemistry, or catalysis.
- Experience with total scattering and PDF methods.
BNL policy requires that research associate appointments be made to individuals who have received their doctorate within the past five years.
At Brookhaven National Laboratory we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Our benefits program includes, but is not limited to:
- Medical Plans
- Dental Plans
- Life Insurance
- 401(k) Plan
- Paid Parental Leave
- Swimming Pool, Weight Room, Tennis Courts, and many other employee perks and benefits
Brookhaven National Laboratory and the Energy and Photon Sciences Directorate are committed to your success. We offer a supportive work environment and the resources necessary for you to succeed.
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