Postdoctoral Appointee – Randomized Algorithms for Optimal Experimental Design and Data Compression

The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory is seeking candidates to apply to a postdoctoral position in the area of Randomized Algorithms, Optimal Experimental Design, Bayesian inverse problems, and Tensor-based data compression. 

The position will address software/algorithm development and/or theory in areas of interest to the applied mathematics, numerical software, and statistics group. In this role, the postdoctoral candidate will work on multi-disciplinary problems and will collaborate with applied mathematicians, computer scientists, and domain specialists. Additionally, you will have access and opportunity to work on state-of-the-art high-performance computing (HPC) resources at Argonne’s Leadership Computing Facility.

Position Requirements

• Recent or soon-to-completed PhD (within the last 0-5 years) in applied mathematics, statistics, computer science, industrial engineering or related field
• Expertise in two or more of the following areas: Randomized Algorithms, Data Assimilation, Optimal Experimental Design, and numerical solution of partial differential equations, and Numerical Optimization
• Knowledgeable in one or more of the following areas: software development in numerical PDEs, Data Assimilation, and Numerical Optimization
• Proficient in one scientific programming language (e.g., C, C++, Fortran, Python, or Julia)
• Experience with Julia, Python, parallel computing, large-scale computational science, and simulation of networked physical systems is a plus
• Ability to model Argonne’s core values of impact, respect, integrity, safety and teamwork

Job Family

Postdoctoral Family

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

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