Postdoctoral Appointee - Computational Mathematics in Energy and Environmental Systems
Argonne National Laboratory
Lemont, IL
Job posting number: #7088957 (Ref:ANL-411852-1)
Posted: November 12, 2021
Application Deadline: Open Until Filled
Job Description
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for multiple postdoctoral positions in the areas of optimization, applied mathematics, statistics, and scientific computing. Several of these positions are connected with the recently awarded DOE project “MACSER: Multifaceted Mathematics for Rare, High Impact Events in Complex Energy and Environment Systems”. The positions will address software/algorithm development and/or theory in areas of interest to the applied mathematics and numerical software group.
Position Requirements
Nonlinear optimization, mixed-integer (linear/nonlinear) optimization, stochastic/robust optimization, and dynamic programming. Bilevel programming and mathematical programming with equilibrium constraints. Data analysis, applied statistics, sampling, and spectral estimation. Parallel algorithms for scientific and high-performance computing. Also required is considerable knowledge in algorithms and/or software development for numerical optimization.
Good proficiency levels in scientific programming languages (e.g., C, C++) are also highly desired. Experience with Julia, parallel computing, large-scale computational science, energy systems and/or environmental applications is a plus.
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeArgonne 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.