Power System Operations & Grid Reliability Workshop Trainer

Volunteering Teaching & Training IT & Telecom

Contract

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UNDP ICPSD will implement the Future Tech Leaders (FTL) programme in Syria as a structured training initiative for final-year engineering students and recent graduates at Damascus University. The programme will build industry-relevant AI skills for climate applications through technical training, applied learning, and specialized tracks.

Participants will also engage in discipline-specific workshops to apply AI skills within engineering domains after the Bootcamp training. These include smart grid modelling for electrical engineering, AI-driven automation systems for computer engineering, and IoT-based climate monitoring systems for electronics and communications engineering.

The Online Volunteer will develop the content for Power System Operations and Grid Reliability Workshop (up to three sessions) and deliver this workshop to the FTL Syria beneficiaries.

We are recruiting 1 Online Volunteer to deliver the Power System Operations & Grid Reliability Workshop for the Future Tech Leaders Syria programme under the guidance of the team focal point.

The Online Volunteer will: • Develop and technical training materials, workshop content, presentations, exercises, assessments, and participant resources required for these workshops and related activities for Power System Operations and Grid Reliability Workshop. • Deliver the Power System Operations and Grid Reliability Workshop to the beneficiaries (up to three sessions). • Prepare the evaluation report and gather feedback for areas of improvement for these sessions • Prepare concise implementation evaluation reports summarizing all activities conducted, participation levels, key achievements, challenges encountered, and recommendations for future programme delivery.

• A minimum of 5 years (with Master's degree) or 7 years (with Bachelor's degree) of professional experience in power systems engineering, grid operations, energy systems modelling, or the application of AI/data-driven methods to the energy sector. • Demonstrated experience in power system modelling, simulation and analysis, including load flow, contingency and reliability analysis, using industry-standard tools (e.g. PSS®E, DIgSILENT PowerFactory, ETAP, MATLAB/Simulink, or open-source equivalents such as PyPSA or PandaPower).[V6.1] • Proven experience in smart grid technologies, including renewable and distributed energy resource integration, grid monitoring and control systems, and grid resilience or climate stress-testing studies. • Practical experience in applying AI/machine learning methods to power and energy applications, such as load and renewable generation forecasting, fault detection and diagnosis, predictive maintenance, or AI-driven automation and control of energy systems. • Working knowledge of Python and open-source scientific libraries (e.g. NumPy, Pandas, Scikit-Learn, TensorFlow/PyTorch) for energy data analysis and modelling. • Previous experience working with UN/UNDP or other international development organizations is an advantage.

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Added 6 days ago - Updated 5 hours ago - Source: unv.org