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Machine Learning Nuclear Data Scientist

Job ID 2306 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.

Organizational Overview
Brookhaven National Laboratory’s Department of Nuclear Science and Technology conducts research and development related to nuclear technologies (reactors and accelerator-driven systems), reliability and risk assessment, and advanced modeling techniques for reactor simulation and energy systems.

The Department serves as a resource in these and related areas to support the missions of the Department of Energy (DOE), the Nuclear Regulatory Commission (NRC), and other national and international organizations. With a world-class staff of professionals with expertise in a broad range of areas related to the design and analyses of commercial, research and advanced nuclear systems, Brookhaven’s capabilities and facilities are also available to support and execute experiments in support of these missions.

The National Nuclear Data Center (NNDC), a part of of BNL’s Nuclear Science and Technology Department, is the largest member of the US Nuclear Data Program (USNDP), whose mission is to provide current, accurate, authoritative data for workers in pure and applied areas of nuclear science and engineering. This is accomplished primarily through the compilation, evaluation, dissemination, and archiving of extensive nuclear datasets. USNDP also addresses gaps in the data, through targeted experimental studies and the use of theoretical models.
The NNDC is responsible for the Nuclear Science Reference (NSR), eXperimental Unevaluated Nuclear Data List (XUNDL), Evaluated Nuclear Structure Data File (ENSDF) and Evaluated Nuclear Data File (ENDF) libraries, as well as the Nuclear Data Sheets journal.   The NNDC is also the main contributor to the EXFOR library.  Web dissemination of these libraries is also one of the main activities at the NNDC.

Position Description
The National Nuclear Data Center has an opening for an Assistant Scientist in nuclear structure evaluations and research.   Applicants will be expected to work on all aspects of the Evaluated Nuclear Structure Data File (ENSDF), including the development of a new format and ancillary codes, compilation and evaluation of nuclear structure and decay data, as well as experimental or theoretical research aligned with ENSDF priorities. This position has a high level of interaction with an international and multicultural scientific community

Position Requirements

Essential Duties and Responsibilities

  • Perform a critical review of experimental data and provide recommended values to be included in the ENSDF database.
  • Extract and vet data from recent publications for inclusion in the XUNDL database.
  • Assist in the development of the next generation ENSDF format and develop applications that apply Machine Learning techniques to the new format.    
  • Participate in and analyze experiments related to the ENSDF database and/or perform theoretical calculations to complement the nuclear structure experimental program

Required Knowledge, Skills, and Abilities:

  • PhD in experimental or theoretical low-energy nuclear physics
  • Minimum of at least two years of full time relevant post-doctoral experience
  • Demonstrated expertise in at least one of the following areas (a) low-energy nuclear spectroscopy, (b) theoretical nuclear structure models
  • Solid publication record in peer-reviewed journals
  • Programming and computing skills such as knowledge of C++, JAVA or Python languages
  • Clear and concise oral and written communication skills.   Applicant will be expected to prepare and deliver oral presentations, as well as write articles in scientific journals

Attention to detail

Preferred Knowledge, Skills, and Abilities:

  • Familiarity with the ENSDF database
  • Experience with Machine Learning algorithms applicable to physical sciences

Other:

  • The incumbent must be available to start by January 2, 2021
  • The position is for a 2-year term, with possible annual renewal contingent upon satisfactory performance and continued funding
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
  • Vacation
  • Holidays
  • Life Insurance
  • 401(k) Plan
  • Retirement Plan
  • Paid Parental Leave
  • Swimming Pool, Weight Room, Tennis Courts, and many other employee perks and benefits

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

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