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Predoctoral Appointee - Scientific Machine Learning and Uncertainty Quantification

at Argonne National Laboratory in Lemont, Illinois, United States

Job Description

The Laboratory for Applied Mathematics, Numerical Software, and Statistics (LANS) and the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invite candidates to apply for a predoctoral position in the area of scientific machine learning and uncertainty quantification.

The position will address software/algorithm development and/or theory in areas of interest to the applied mathematics, numerical software, and statistics group. This Predoctoral Appointee will have the opportunity to carry out simulations on some of the world’s fastest supercomputers and collaborate with other computer scientists and mathematicians at the MCS division.

For more information on the applied mathematics, numerical software, and statistics group at Argonne, see https://www.anl.gov/mcs/lans

Position Requirements

Required skills and qualifications:

+ Recent Masters degree (or soon-to-be-completed in 2024) in applied mathematics, statistics, computer science, industrial engineering or related field.

+ Expertise in two or more of the following areas: inverse problems, nonlinear optimization, stochastic optimization, uncertainty quantification, parallel and distributed computing algorithms for scientific and high-performance computing, and numerical solution of differential equations.

+ Knowledgeable in one or more of the following areas: software development in SciML, software development in numerical optimization, statistics, and/or development of large-scale stochastic control algorithms.

+ Proficiency in one scientific programming language (e.g., C, C++, Fortran, Python, or Julia).

+ Ability to model Argonne’s core values of impact, respect, integrity, safety and teamwork.

Preferred skills and qualifications:

+ Experience with Julia, Python, parallel computing, large-scale computational science, and simulation of networked physical systems.

Job Family

Temporary Family

Job Profile

Predoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne’s Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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Job Posting: JC263508736

Posted On: Aug 01, 2024

Updated On: Aug 03, 2024

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