Postdoctoral Research Associate

Texas A&M-posted 4 days ago
Full-time
Galveston, TX
251-500 employees
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The Department of Marine Engineering Technology of Texas A&M University seeks a Postdoctoral Research Associate for an immediate start to advance modeling, control, and optimization of power and energy systems with applications to maritime and coastal infrastructures (e.g., shipboard microgrids, port facilities, islanded communities, desalination plants). The associate will develop rigorous, scalable methods—spanning physics-based and data-driven models—for optimal power flow, demand response of flexible loads, transient/stability-aware dispatch, and cybersecurity-resilient control. The role includes leading publications, contributing to proposals, mentoring students, and collaborating with academic, utility, and industry partners.

  • Research and Development Formulate and analyze models for transmission/distribution, microgrids, and shipboard power systems (steady-state and dynamic).
  • Design optimization and control algorithms (convex/nonconvex, stochastic/robust, MPC) for real-time dispatch, frequency regulation, and DER coordination.
  • Integrate data-driven and physics-informed approaches for state estimation, forecasting, and anomaly detection.
  • Build simulation pipelines and, where applicable, hardware-in-the-loop or lab prototypes; manage datasets and reproducible code.
  • Academic Writing Lead and co-author journal and conference papers; present results at professional venues.
  • Contribute to proposal writing and project reporting, coordinate with sponsors and collaborators.
  • Mentoring Mentor undergraduate/graduate researchers; support occasional instructional activities aligned with the lab’s mission.
  • Ph.D. in Electrical/Mechanical Engineering, Computer Science, Industrial Engineering, or a related field (by start date).
  • Strong background in power systems analysis (OPF, state estimation) and numerical optimization/control.
  • Proficiency with Python/MATLAB and power-system toolchains (e.g., MATPOWER/OpenDSS).
  • Demonstrated research record (publications, open-source code, or equivalent).
  • Solid knowledge of power-system analytical methods (power flow, economic dispatch, state estimation);
  • Proficiency in machine learning and Python programming;
  • Strong scholarly writing skills with a demonstrated publication record and fluency in LaTeX compilers;
  • Excellent verbal and written communication for collaboration, presentations, and mentoring.
  • Experience with microgrids/shipboard power, demand response of flexible loads, and grid cyber-physical security.
  • Expertise in data-driven modeling (ML for energy, forecasting, anomaly detection) and physics-informed learning.
  • Real-time/HIL or embedded control experience (e.g., OPAL-RT, RTDS) and laboratory integration.
  • Strong communication skills and a collaborative mindset.
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