Machine learning applications for CO2 reduction in power-intensive industries

#2022-MLE-006

At Predictive Layer (PL), we develop and industrialize Machine Leaning (ML) models for highly energy intensive industries such as steel production. The forecasts provided by the ML models are used to optimise key activities such as production scheduling or power purchase.

The objective of the internship will be to develop an automatic system that allows minimising the CO2 emissions to PL’s customers.

Our scale up company is leading automated modeling & investments based on AI & ML & Deep Learning in several industries and financial markets. We were rewarded as finalist in the EY Entrepreneur of the Year 2019 in Switzerland. We are scaling our team to expand further our activities. We are looking for passionate individuals who wants to work on advanced computational engineering, mixing latest mathematics (Machine Learning, DL,…), Computing (Cloud & Open data) on sophisticated enterprise & financial markets within a young and highly international teams with massive international engagement.

The ideal candidate for this 4-6 months of internship:

• Student in EPFL Master of Computer Science or Data Science
• Supervised and unsupervised machine learning
• Principal component analysis, neural networks, linear models
• Programming languages: python
• Libraries: scikit-learn, pandas, tensoflow, keras.
• Professional knowledge of English (advanced)