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UID:submissions.supercomputing.org_SC23_sess503_job179@linklings.com
SUMMARY:Postdoctoral Researcher – Mathematical Optimization for Energy Sys
 tems
DESCRIPTION:APPLY Online at:  https://nrel.wd5.myworkdayjobs.com/en-US/NRE
 L/job/Postdoctoral-Researcher---Mathematical-Optimization-for-Energy-Syste
 ms_R11489\n\nThe Complex Systems Simulation and Optimization (CSSO) Group 
 in the NREL Computational Science Center has an opening for a full-time Po
 stdoctoral Researcher – Computational Science, with emphasis on mathematic
 al optimization and its application to the design and control of energy sy
 stems. We are looking for a dynamic researcher with a strong technical bac
 kground to help us transform our renewable energy future through advanced 
 automation, control and decision making.\n\nThe successful candidate will 
 have extensive experience with mathematical optimization formulations and 
 algorithms and their application to physical systems. Additionally, the ca
 ndidate will be familiar with parallel algorithmic approaches for large-sc
 ale linear, nonlinear, integer, and stochastic optimization problems. We a
 nticipate that the research will involve integrating Artificial Intelligen
 ce (AI) techniques, such as reinforcement learning (RL), with classical ma
 thematical optimization approaches and implementations. We seek candidates
  capable of pursuing research directions that combine these algorithmic co
 mponents, using implementations that are suitable for effective utilizatio
 n of the modern parallel computing architectures that are available at NRE
 L. Candidates with creative problem-solving skills, interest in cross-disc
 iplinary collaboration, and a passion for the mission and goals of both NR
 EL and EERE are of particular interest.\n\nResponsibilities:\n\nCollaborat
 e with domain experts to identify where mathematical optimization constitu
 tes a viable approach and maintain awareness of optimization-related resea
 rch both at NREL and in the literature more generally.\nAdopt existing – o
 r develop new – mathematical, computing, and simulation frameworks require
 d to implement and evaluate the performance of optimization algorithms and
  solutions.\nCreatively identify new opportunities to leverage AI/RL to au
 gment or enhance classical optimization algorithms and/or formulations.\nA
 uthor publications and contribute to proposals to sustain research directi
 ons.\n\n
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