Organisation Name: Brookhaven National Laboratory (BNL)
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Country: United States
Job Description:
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 (BNL) is a scientific, extreme scale Data Laboratory in the U.S., New York State, Long Island. We have a lively, fast-growing data science research program at BNL, with a specific focus on the challenges presented by the analysis, interpretation, and use of data at extreme scales and in real-time. The data science program is accompanied by significant computational modeling research effort, in support of the design, planning, analysis, and interpretation of both laboratory and computer experiments and their results. The Computational Science Initiative (CSI - https://www.bnl.gov/compsci/) provides a laboratory-wide umbrella for these activities, bringing together computer scientists, applied mathematicians, and domain scientists to carry out leading-edge research, convert research results into practical solutions that advance domain science, and provide the necessary computing infrastructure services and training to support efficient operation. The position will reside within CSI’s Applied Mathematics group, which conducts research on a variety of applied science and engineering problems involving methods such as optimal experimental design, uncertainty quantification, decision making under uncertainty, modeling and simulation, surrogate and reduced order modeling, extreme-scale data analysis, and scientific machine learning.
Position Description
The Applied Mathematics Group of the Computational Science Initiative (CSI) at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for a post-doctoral research associate position in applied mathematics, machine learning, and scientific computing. This position offers a unique opportunity to conduct research in emerging interdisciplinary research problems at the intersection of applied mathematics, machine learning, and high-performance computing (HPC) with applications in diverse scientific domains of interest to BNL and the Department of Energy (DOE). Topics of specific interest include: (i) optimal decision-guided data reduction; (ii) feature extraction/engineering in high-dimensional compositional workflows that involve machine learning (ML) models; (iii) Bayesian inference and uncertainty quantification in scientific ML models; (iv) learning/optimization of low-dimensional latent feature spaces for ML surrogates. The position includes access to world-class HPC resources, such as the BNL Institutional Cluster and DOE leadership computing facilities. Access to these platforms will allow computing at scale and will ensure that the successful candidate will have the necessary resources to solve challenging DOE problems of interest.
This program provides full support for a period of two years at CSI with possible extension. Candidates must have received a doctorate (Ph.D.) in applied mathematics, statistics, computer science, or a related field (e.g., mathematics, engineering, operations research, physics) within the past five years. This post-doc position presents a unique chance to conduct interdisciplinary collaborative research in BNL programs with a highly competitive salary.
Essential Duties and Responsibilities:
Conduct research in various applied mathematics/machine learning problems in the context of scientific data reduction in compositional workflows.
Work in interdisciplinary collaborations with applied domain scientists on various aspects of scientific data generation, processing, and compression.
Formulate a high-quality research program in collaboration with mentors in the group.
Position Requirements
Required Knowledge, Skills, and Abilities:
Ph.D. in applied mathematics, statistics, computer science, or a related field (e.g., mathematics, engineering, operations research, physics) awarded within the last 5 years
Programming experience in machine learning, scientific modeling, or scientific computing.
Experience in scientific ML applied to domain sciences problems (e.g., in physical sciences, life sciences, or engineering)
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:
Brookhaven Science Associates requires proof of a COVID-19 vaccination for all employees. Proof of full vaccination as recognized by the CDC and/or WHO, inclusive of the two-week waiting period, is required at the start of your employment.
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.
