Assistant Computational Mathematician/Statistician
Job posting number: #7098598 (Ref:413032)
Posted: April 14, 2022
Application Deadline: Open Until Filled
Research and development of uncertainty quantification algorithms and data analysis for models of physical and complex systems. This will include research in uncertainty representation and propagation; optimization, data assimilation, and inference for large-scale applications; and scalable methods and software for the analysis and calibration using very large data sets resulting from dynamical simulation. Applications include epidemiology, urban systems, new materials design, and physics of galaxy formation. Participate at all the stages of the implementation of the resulting methods from prototyping in high-level languages to the development in a high-performance computing environment. Part of a team that includes computational scientists, statisticians, computer scientists and domain scientists.
Knowledge, Skills and Experience
Knowledge in the following three areas: (1) uncertainty quantification and statistical analysis and modeling techniques such as data assimilation, Bayesian analysis, Gaussian process modeling; (2) stochastic optimization algorithms, single- and multi-objective, and decomposition techniques; and (3) generation of synthetic populations including network modeling.
Expertise in computational statistics and uncertainty quantification (Bayesian analysis, data assimilation, Gaussian process modeling), and their application to complex systems modeling.
Experience in statistical algorithms and software for large-scale scientific applications.
Expertise in programming in a high-level language R or Python.
Expertise in MPI bindings in R (Rmpi) or Python (MPI4Py) and C/C++ native code extensions for R (Rcpp) and Python (Cython).
Experience and skills in interdisciplinary research involving mathematicians, computational scientists, and discipline scientists.
Should be able to interact with members of a multidisciplinary team.
Collaborative skills, including the ability to work well with scientists at other laboratories and universities.
Should be able to develop, under supervision, high-quality scientific reports.
Independent judgment and the ability to abstract from specific problems to general solutions.
Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
RD2: Bachelor's & 5+ yrs, Master's & 3+ yrs or Doctorate & 0 yrs
Job FamilyResearch Development (RD)
Job ProfileMathematics/Statistics 2
Time TypeFull time
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