Job ID 2367 Date posted 10/19/2020
Brookhaven National Laboratory (www.bnl.gov) delivers discovery science and transformative technology to power and secure the nation’s future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy’s (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University.
The CFN is a DOE-funded national scientific user facility, offering users a supported research experience with top-caliber scientists and access to state-of-the-art instrumentation. The CFN mission is advancing nanoscience through frontier fundamental research and technique development, and is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users.
Three strategic nanoscience themes underlie the CFN scientific facilities: The CFN fosters research on complex self-assembly processes, for building new ways of constructing Synthesis byNanomaterial Assembly. The CFN researches and applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery for target structure and functionality. The CFN develops and utilizes advanced capabilities for studies of Nanomaterials in Operando Conditions for characterizing materials and reactions at the atomic scale in real-world environments.
The CFN is seeking an exceptional Postdoctoral Research Associate to contribute to a multidisciplinary project involving several DOE user facilities, focusing on accelerating materials discovery from complex multi-modal experimental and simulated data setthrough application of Artificial Intelligence and Machine Learning techniques (AI/ML). In this position, you will employ software engineering, machine learning methods, and modelling to develop data processing and interpretation pipelines for handling the streamed data from a suite of in situ / operando experimental facilities. As a first implementation, you will apply these methods for processing and interpreting data from X-ray spectroscopy measurements. You will use the data pipelines you develop to condition the data, extract valuable scientific information and provide real-time feedback to the experiment. In this research, you will work on data analytics closely coupled with in situ / operando experiments under the supervision of Xiaohui Qu, in close collaboration with researchers at the National Synchrotron Light Source II, CFN, and the Brookhaven Computational Science Initiative.
Required Knowledge, Skills, and Abilities
You are qualified for this Research Associate position if:
- You have earned a Ph.D. in a relevant discipline (Materials Science, Physics, Chemistry, or a related engineering discipline) within the past five years or will complete your degree prior to the starting date;
- You have a strong background in machine learning model training with applications to domain science problems;
- You have demonstrated experience of software development and/or data analytics through publications, GitHub repository records, or other public communication;
- You are committed to fostering an environment of safe scientific work practices.
Preferred Knowledge, Skills and Abilities
You are well-matched to this position if:
- You have experience with non-SQL database architecture, e.g. MongoDB, Redis.
- You work effectively in aninterdisciplinary team to tackle challenging scientific problems, particularly the application of data analytics to understand experimental results;
- You have working knowledge of spectroscopic data processing and deep learning methods;
- You are interested in learning state-of-the-art deep learning and data analytics advances;
- You communicate effectively, verbally and in writing.
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, Dental, and Vision Care Plans
- Flexible Spending Accounts
- Paid Time-off and Leave Programs (vacation, holidays, sick leave, paid parental leave)
- 401(k) Plan
- Flexible Work Arrangements
- Tuition Assistance, Training and Professional Development Programs
- Employee Fitness/Wellness & Recreation: Gym/Basketball Courts, Weight Room, Fitness Classes, Indoor Pool, Tennis Courts, Sports Clubs/Activities (Basketball, Ping Pong, Softball, Tennis)
Brookhaven National Laboratory (BNL) is an equal opportunity employer that values inclusion and diversity at our Lab.We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class.
BNL takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities.We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.Please contact us to request accommodation.
*VEVRAA Federal Contractor
Brookhaven employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. The full text of the Order may be found at: https://www.directives.doe.gov/directives-documents/400-series/0486-1-border/@@images/file
To apply for this job please visit jobs.bnl.gov.