The Mathematics and Computer Science Division at Argonne National Laboratory seeks well-prepared candidates in applied mathematics, numerical analysis, optimization, numerical software, and statistics for multiple positions at career levels from postdoctoral researchers to senior staff researchers.

Please note, this is an “Evergreen” job posting which is used to build a pool of candidates for anticipated critical positions within the division. We do not interview or hire from an evergreen posting; however, you may be invited by a Talent Acquisition Specialist to apply to a specific job posting in the near future.

The positions will address software/algorithm development and/or theory in areas of interest to the applied mathematics, numerical software, and statistics group. Candidates should have expertise in one or more of the following areas:

• Nonlinear optimization, including mixed-integer, multiobjective, stochastic/robust, PDE-constrained, simulation-based, dynamics, derivative-free, and parallel/concurrent optimization
• Machine learning, data analysis, applied statistics, and uncertainty quantification
• Statistical inference and analysis, sampling, spectral estimation
• Stochastic processes, stochastic differential equations
• Data assimilation, inverse problems
• High-order methods for PDEs/CFD including spectral element methods
• Numerical linear algebra focusing on highly scalable preconditioners including matrix-free methods
• Numerical methods for ordinary and partial differential equations including error estimators and adjoints
• Automatic/algorithmic differentiation
• Quantum information sciences, including quantum computing, networking, and simulation

Position Requirements

• Applicants should have a master’s or doctorate degree in computer science, mathematics, operations research, statistics, or a related discipline.
• Applicants should have documented expertise commensurate with their experience, in computational mathematics, computational science, or numerical libraries.
• Programming experience in C, Fotran, Julia, Python or another programming language is desirable; experience with parallel computing is desirable.
• The appointment level will be commensurate with experience.

More information on applied mathematics, numerical software, and statistics work at Argonne may be found at https://www.anl.gov/mcs/lans .

Argonne provides a collaborative, open-science environment where scientists from various disciplines are engaged in solving challenging fundamental and practical problems. We value and strive for diversity in backgrounds, experiences, and perspectives. At Argonne, one also has access to extreme-scale computing and experimental facilities.

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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.  

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Please note that all Argonne employees are required to be vaccinated against COVID-19. All successful applicants will be required to provide their COVID-19 vaccination verification as a condition of employment, subject to limited legally recognized exemptions to COVID-19 vaccination.