Home Postdoc Abroad Postdoctoral Researcher – Mathematical Optimization for Energy Systems, (NLR) USA

Postdoctoral Researcher – Mathematical Optimization for Energy Systems, (NLR) USA

Post-Doctoral Fellowship Position at USA, Ozbolat Laboratory at Penn State

The Advanced Computing Solutions Group in the National Laboratory of the Rockies (NLR) Computational Science Center is seeking a dedicated and technical Postdoctoral Researcher to join their team. This role focuses on applying mathematical optimization to the design and control of energy systems to help transform the future of energy.

Postdoctoral Researcher – Mathematical Optimization for Energy Systems, (NLR) USA


Job Overview

FieldDetails
DesignationPostdoctoral Researcher
Research AreaMathematical Optimization for Energy Systems
LocationGolden, CO
Employment TypeFull-time (Fixed Term)
Annual Salary Range$76,600 – $126,400

Job Description

As a Postdoctoral Researcher, you will collaborate with domain experts to identify, develop, and evaluate mathematical, computing, and simulation frameworks for energy systems. You will work on:

  • Optimization Formulation: Applying mathematical optimization formulations and algorithms to physical systems.
  • Algorithmic Innovation: Designing parallel algorithmic approaches for large-scale linear, nonlinear, integer, and stochastic optimization problems.
  • AI Integration: Identifying opportunities to leverage Artificial Intelligence (AI) and Reinforcement Learning (RL) to augment or enhance classical optimization algorithms.
  • Research Output: Authoring publications and contributing to research proposals to sustain future research directions.

Eligibility & Qualifications

Basic Qualifications:

  • Must be a recent PhD graduate (within the last three years).
  • Must meet educational requirements prior to the employment start date.

Required Skills:

  • Experience formulating optimization problems in algebraic modeling languages (e.g., Pyomo, JuMP, PuLP, GAMS).
  • Experience with mathematical optimization solvers (e.g., CPLEX, Gurobi, Xpress, Cbc, Ipopt) and their capabilities.
  • Strong understanding of optimization fundamentals (both computational and mathematical).

Preferred Qualifications:

  • Familiarity with distributed computing frameworks such as MPI and OpenMP.
  • Proficiency in programming with Python and/or Julia.
  • Experience with scalable machine learning frameworks (e.g., PyTorch).
  • Experience working in diverse, inclusive, and cross-disciplinary research teams.

How to Apply

To be considered for this position, you must submit an application form through the official NLR Careers portal. Please ensure you include both a cover letter and a resume/CV with your application.

Last Date to Apply

Open Now

The anticipated closing window for application submission is 30 days from the initial posting, though this may be extended as needed. It is recommended to apply as soon as possible.

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