Postdocs position available: Exploration of deep learning methods for renewable energy forecasting.
Prof. Yoshua Bengio and Prof. Loubna Benabbou are looking for 2-year postdoc working at Mila sponsored by the Quebec Ministry of the Environment and Fight Against Climate Change, in the area of renewable energy forecasting. Individuals applying for this position should have a solid background in development of deep learning models and an interest in machine learning for physical modeling and forecasting.
The aim is to develop and integrate multiple deep learning algorithms to effectively forecast renewable energy sources while extracting predictive features from various heterogeneous sources of data (weather, radiation, geographical position). A challenge is to develop a unified prediction model for different time horizons including a probabilistic quantification of uncertainty in future trajectories.
The individual should ideally have a combination of experience and interest in this topic as well as an established track record in deep learning. The candidate is expected to carry out research on assigned project(s). The candidate will also have an opportunity to supervise junior researchers.
– Development of renewable energy resource and energy generation forecasting models
– Collaborate with machine learning and renewable energy experts on the project
– Supervise junior researchers
– Write scholarly articles and present the results of the project in scientific conferences
The ideal candidate will have the following qualifications:
– A PhD degree in a related field (computer science, machine learning, engineering, etc.) received in the last 3 years
– Strong background in machine learning, particularly deep learning, math and statistics
– Strong programming skills in python
– Good spoken and written communication skills in English.
Please apply using the form on this page: https://mila.quebec/en/admission-process-for-postdocs/ and contact email@example.com to let Yoshua Bengio know about your application.