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Research Opportunity
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Research Opportunity

Computational intelligence for forecasting and optimization in energy systems


Work description

The technological revolution in the energy sector is producing large volumes of data with valuable impact in the business and functional processes of system operators, generation companies and grid users. The research fellow will develop innovative data-driven techniques (e.g., reinforcement learning) for different optimization problems (e.g., energy efficiency) and join a multidisciplinary team referenced internationally for its high expertise in energy analytics, within the context of smart grids.

Academic Qualifications

Master degree in Electrical Engineering, Computer Science, Operations Research or similar

Minimum profile required

- Advance knowledge in machine learning- Advance knowledge in programming (e.g., Python)- Fluent in English (spoken and written)

Preference factors

- Experience with energy systems related problems - Experience with optimization techniques (mathematical, meta-heuristics or data-driven) - Experience with TensorFlow or PyTorch

Application Period

Since 06 Aug 2019 to 20 Aug 2019


Cluster / Centre

Power and Energy / Power and Energy Systems

Scientific Advisor

Ricardo Jorge Bessa