Research Fellow, Energy Analytics/Artificial Intelligence/Machine Learning/DER Management

Nov 22, 2020
End of advertisement period
Dec 22, 2020
Contract Type
Full Time

Energy Research Institute @ NTU invites applications for the position of Research Fellow.

Key Responsibilities:

  • Design and develop deep learning/AI-powered DER analytics & renewable energy/price/load forecasting tools VPP operation
  • Interval forecasting for sources & load forecasting tools suited to small geographical areas (e.g., at the level of customers or aggregation areas) to capture the uncertainty, and adequately addressing the requirements of robust/stochastic optimization formulations
  • Research into state-of-the-art solutions in AI-powered DER analytics, deep learning architectures, and generate innovative ideas that can be implemented for VPP management
  • Be a hands-on technologist and domain/industry expert in commercial solution development, system integration & implementation
  • Be an R&D team lead to define & achieve the project goals
  • Work closely with researchers, developers, partners and/or external vendors for timely project delivery
  • Any other ad-hoc duty or responsibility; e.g., project presentation, progress report preparation, procurement and research collaborations etc. assigned by the project supervisor

Job Requirements:

  • PhD degree in Electrical and Electronics Engineering or Computer Science/Engineering, specialized in Energy Analytics/Artificial Intelligence/Machine Learning/DER management
  • Solid knowledge and experience in Artificial Intelligence/Reinforcement Learning-based analytics & forecasting for distribution resource operations and energy management
  • Proven skills in Machine Learning (Supervised/Unsupervised/Semi-supervised/Reinforcement Learning); e.g., linear/logistics regression discriminant analysis, bagging, Support Vector Machine (SVM), Random Forest (RF), Bayesian model, neural networks, etc
  • Programming languages (e.g., R, Python) in view of the abovementioned analytical concepts and techniques
  • Strong skills in the use of one or more of current state of the art machine learning frameworks such as Scikit-Learn, H2O, Keras, Pandas, Numpy, TensorFlow and Spark, etc
  • Excellent verbal and written communication skills in English
  • Strong analytical and conceptual abilities
  • Able to work independently and in a team to realize the proposed works

We regret that only shortlisted candidates will be notified.

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