Posting Title
Postdoctoral Researcher – Mathematical Optimization for Energy Systems.

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Location
CO - Golden

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Position Type
Postdoc (Fixed Term)

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Hours Per Week
40

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Working at NREL
The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.

From day one at NREL, you’ll connect with coworkers driven by the same mission to save the planet. By joining an organization that values a supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our eight employee resource groups, numerous employee-driven clubs, and learning and professional development classes.

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Note: Research suggests that potential job seekers may self-select out of opportunities if they don't meet 100% of the job requirements. We encourage anyone who is interested in this opportunity to apply. We seek dedicated people who believe they have the skills and ambition to succeed at NREL to apply for this role.

Job Description

The Complex Systems Simulation and Optimization (CSSO) Group in the NREL Computational Science Center has an opening for a full-time Postdoctoral Researcher – Computational Science, with 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 renewable 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 at NREL. Candidates with creative problem-solving skills, interest in cross-disciplinary collaboration, and a passion for the mission and goals of both NREL and EERE are of particular interest.

Responsibilities:

• Collaborate with domain experts to identify where mathematical optimization constitutes a viable approach and maintain awareness of optimization-related research both at NREL 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.

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Basic Qualifications
Must be a recent PhD graduate within the last three years.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• 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.

Preferred Qualifications

• 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, PyTorch
• Experience working with diverse, inclusive, and cross-disciplinary research teams

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Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $71,300 - $117,600

NREL takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.

Benefits Summary
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. NREL 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.

* Based on eligibility rules

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NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

Submission Guidelines

Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

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EEO Policy

NREL is an Equal Opportunity/Affirmative Action Employer. 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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