Postdoctoral Researcher – Mathematical Optimization Energy Systems

Postdoctoral Researcher – Mathematical Optimization for Energy Systems

Location: CO - Golden

Position Type: Postdoc (Fixed Term)

Hours Per Week: 40

The Advanced Computing Solutions Group in the NLR Computational Science Center has an opening for a full-time Postdoctoral Researcher – Computational Sciences, with an emphasis on mathematical optimization and its application to the design and control of energy systems. We are looking for a dynamic researcher with a strong technical background to help us transform our energy future through advanced automation, control and decision making.

The successful candidate will have extensive experience with mathematical optimization formulations and algorithms and their application to physical systems. Additionally, the candidate will be familiar with parallel algorithmic approaches for large-scale linear, nonlinear, integer, and stochastic optimization problems. We anticipate that the research will involve integrating Artificial Intelligence (AI) techniques, such as reinforcement learning (RL), with classical mathematical optimization approaches and implementations.

We seek candidates capable of pursuing research directions that combine these algorithmic components, using implementations that are suitable for effective utilization of the modern parallel computing architectures that are available didates with creative problem-solving skills, interest in cross-disciplinary collaboration, and a passion for the mission and goals of both NLR and CMEI are of particular interest.

• Collaborate with domain experts to identify where mathematical optimization constitutes a viable approach and maintain awareness of optimization-related research both at NLR and in the literature more generally.
• Adopt existing – or develop new – mathematical, computing, and simulation frameworks required to implement and evaluate the performance of optimization algorithms and solutions.
• Creatively identify new opportunities to leverage AI/RL to augment or enhance classical optimization algorithms and/or formulations.
• Author publications and contribute to proposals to sustain research directions.

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

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

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

Job Profile:
Postdoctoral Researcher / Annual Salary Range: $76,600 - $126,400

Benefits include medical, dental, and vision insurance; short-term disability insurance; pension benefits; 403(b) Employee Savings Plan with employer match; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement-based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement.

All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

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