The Machine Learning Group of the Computational Science Initiative at BrookhavenNational Laboratory (BNL) invites exceptional candidates to apply for a post-doctoral researchassociateposition in computational modeling and machine learning.This position offers a unique opportunity to conductboth basic and applied research in concert with collaborators working on diverse scientificandsecurity problems of interest to BNL and the Department of Energy (DOE).

Topics of particular interest include: (i) first-principles modeling as applied to energy storage and (ii) scientific machine learning for accelerating simulations and analyzing data. The successful candidate will work with scientists across multiple other departments at BNL, including the Interdisciplinary Science Department, Center for Functional Nanomaterials, and National Synchrotron Light Source II.

The position provides access to world-class computing resources, such as the BNL InstitutionalCluster and DOE leadership computing facilities. Access to these platforms will allow computingat scale, and together with access to unique data sources, will ensure that the successfulcandidate has the necessary resources to solve challenging DOE problems of interest. Thesuccessful candidate will join a growing research group with diverse expertise and projectsspanning the full breadth of BNL’s and the DOE’s missions.

This post-doc position presents a unique chance to conduct interdisciplinary collaborative research in BNLprograms with a highly competitive salary.

Essential Duties and Responsibilities:

• Conduct research in electrocatalysis and chemical reaction modeling for energy storage.

• Perform data analysis by applying existing machine learning methods and novel learning algorithms.

• Work in interdisciplinary collaborations with subject matter experts on various aspects ofscientific data generation and processing, and methods evaluation.

• Formulate own high-quality research ideas and directions in collaboration with mentorsin the group.

• Communicate research progress, challenges, and achievements, and engage within andbeyond the group on new potential collaborations.

Required Knowledge, Skills, and Abilities

• Ph.D. in chemistry, computational/theoretical chemistry, condensed matter physics, materials science, or a related field (e.g., chemical, or mechanical engineering) awarded within the last 5 years.

• Strong research experience (e.g., evidenced by publication record).

• Research experience in computational modeling.

Preferred Knowledge, Skills, and Abilities:

• Experience with running first-principles simulations.

• Experience in energy storage-related research.

• Strong expertise in first-principles modeling for heterogeneous electrocatalysis, including thermodynamics and kinetics of reaction energetics.

• Excellent programming skills.

• Practical experience working with machine learning models.

• Experience working in multidisciplinary collaborations.

• Experience with synchrotron characterization data analysis, such as small angle X-ray scattering.

Other Detail:

• Initial 2-year term appointment subject to renewal contingent on performance and funding.
• 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.​
• ​ Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $68400 - $113250 / year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.

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 486.1A. 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-a/@@images/file