Postdoctoral Associate in Numerical Optimization for Design of Experiments
ID: 7196904 (Ref.No. 416874)
Posted: November 30, 2023
The Laboratory for Applied mathematics, Numerical software, and Statistics (LANS) and the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invite applicants for a postdoctoral position in the area of numerical optimization. You will investigate and develop new algorithms for solving dynamic optimization problems with applications to sequential design of experiments, motivated by problems arising from various imaging techniques.
Candidates interested in advancing developments in numerical optimization (especially dynamic optimization), active learning, and design of experiments for challenging large-scale data analysis, with interesting and real applications, will find a stimulating environment at the laboratory. Candidates should have been or soon will be awarded a doctoral degree in applied mathematics, statistics, computer science, machine learning or related areas. Knowledge is desired in one or more of mathematical optimization, inverse problems, scientific computing, and/or machine learning.
- A completed or soon-to-be completed PhD (typically within the last 0-3 years) in mathematics or a related discipline (e.g. computer science, engineering).
- Experience in mathematical optimization, machine/deep learning, and scientific computing.
- Effective verbal and written communication skills.
- Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.
Desirable knowledge and skills:
- Software development practices for large-scale computation and data-intensive problems.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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