Researcher III - Mathematical Optimization for Energy Systems

National Laboratory
Golden, United States of America
31 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 151K

Job location

Golden, United States of America

Tech stack

Artificial Intelligence
IBM ILOG CPLEX Optimization Studio (CPLEX)
Distributed Computing Environment
Python
Machine Learning
OpenMP
TensorFlow
Signal Processing
Reinforcement Learning
High Performance Computing
PyTorch
Parallel Computation
Optimization Algorithms

Job description

The Advanced Computing Solutions Group in the NLR Computational Science Center has an opening for a Computational Science Researcher, 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 at NRL. Candidates 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.

Requirements

Do you have experience in Technical writing within technology?, Do you have a Master's degree?, Relevant PhD . Or, relevant Master's Degree and 3 or more years of experience . Or, relevant Bachelor's Degree and 5 or more years of experience . Demonstrates complete understanding and wide application of scientific technical procedures, principles, theories and concepts in the field. General knowledge of other related disciplines. Demonstrates leadership in one or more areas of team, task or project lead responsibilities. Demonstrated experience in management of projects. Very good technical writing, interpersonal and communication skills.

  • Must meet educational requirements prior to employment start date., * Good understanding of optimization fundamentals, both computational and mathematical.
  • Experience programming in Python and/or Julia
  • Experience with Pyomo and/or JuMP
  • Experience with mathematical optimization solvers, e.g., CPLEX, Gurobi, Xpress, Cbc, Ipopt, and their capabilities.
  • Familiarity with distributed computing frameworks such as MPI and OpenMP
  • Experience with scalable machine learning frameworks, e.g, PyTorch
  • Experience building foundation models for AC-OPF on transmission grids
  • Experience with using machine learning and signal processing techniques for fault detection on microgrids, * Experience working with diverse, inclusive, and cross-disciplinary research teams
  • Experience working on HPC systems

Benefits & conditions

Pulled from the full job description

  • 403(b) matching
  • Tuition reimbursement
  • 403(b)
  • AD&D insurance
  • Health insurance
  • Paid time off
  • Vision insurance, Benefits include medical, dental, and vision insurance; short*- and long-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; paid holidays; and tuition reimbursement*. 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. Limited-term positions are not eligible for long-term disability or tuition reimbursement.

About the company

NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development. Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth. At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being., E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.

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