Postdoctoral Appointee - Randomized Algorithms for Optimal Experimental Design and Data Compression
Argonne National Laboratory
Lemont, USA
Job posting number: #7292939 (Ref:419189)
Posted: November 6, 2024
Job Description
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 FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeAs 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.
Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
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