Computational Mathematician/Statistician
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Argonne National Laboratory
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Lemont, IL
SessionJob Fair
Event Type
Job Posting
TP
W
TUT
XO
TimeMonday, 9 November 20209am - 8pm EDT
Location
DescriptionPosition Description:
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. The appointment level will be commensurate with experience.
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
This is an Evergreen job posting which allows candidates to apply once to be considered for multiple job requisitions; you may be asked to apply to a specific job posting in the future.
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 and comprehensive expertise, commensurate with their experience, in computational mathematics, computational science, or numerical libraries.
Programming experience in C, Python, Fortran, or another programming language is desirable; experience with parallel computing is desirable.
Openings are available immediately, but there is flexibility in start dates for highly qualified candidates. More information on applied mathematics, numerical software, and statistics work at Argonne may be found at https://www.anl.gov/mcs/lans. Feel free to contact members of the LANS group directly by email with specific questions.
About Argonne: Argonne is a multidisciplinary science and engineering research center, where world-class researchers work alongside experts from industry, academia, and other government laboratories to address vital national challenges in clean energy, environment, technology, and national security. We pursue big, ambitious ideas that redefine what is possible. Our pursuit of groundbreaking discoveries pushes the boundaries of fundamental science, applied science, and engineering to solve complex challenges and develop useful technologies that can transform the marketplace and change the world.
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. The appointment level will be commensurate with experience.
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
This is an Evergreen job posting which allows candidates to apply once to be considered for multiple job requisitions; you may be asked to apply to a specific job posting in the future.
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 and comprehensive expertise, commensurate with their experience, in computational mathematics, computational science, or numerical libraries.
Programming experience in C, Python, Fortran, or another programming language is desirable; experience with parallel computing is desirable.
Openings are available immediately, but there is flexibility in start dates for highly qualified candidates. More information on applied mathematics, numerical software, and statistics work at Argonne may be found at https://www.anl.gov/mcs/lans. Feel free to contact members of the LANS group directly by email with specific questions.
About Argonne: Argonne is a multidisciplinary science and engineering research center, where world-class researchers work alongside experts from industry, academia, and other government laboratories to address vital national challenges in clean energy, environment, technology, and national security. We pursue big, ambitious ideas that redefine what is possible. Our pursuit of groundbreaking discoveries pushes the boundaries of fundamental science, applied science, and engineering to solve complex challenges and develop useful technologies that can transform the marketplace and change the world.
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