AI/ML Student Internship

Uren per week


Are you passionate about Artificial Intelligence (AI), Machine Learning (ML) and the energy transition? Then this internship is for you!

Emmett Green is seeking an AI/ML student to join our Energy Management System (EMS) team. As a scale-up company, Emmett Green helps realize energy hubs. Not just by talking about it, but mainly by taking action! This accelerates the energy transition, enables further sustainability, and ensures supply security for governments, industries, SMEs, investors, and developers. Our Energy Management System helps in this by monitoring and controling sustainable energy flow using sensors, a large database and optimization algorithms

As an intern in our EMS team, you will play a key role in this transformative project by improving our existing model for predicting imbalance prices in the energy market. Your primary responsibilities will include:

  • Analyzing factors affecting imbalance prices in the energy market, building on our existing statistical model.
  • Researching and implementing ML/AI methods to improve imbalance price predictions.
  • Collaborating closely with the EMS team to integrate your improved prediction model into our production systems.


  • Enrolled in an AI/ML/Statistics degree program (BSc, MSc)
  • Strong foundation in statistics, probability, and mathematical modelling
  • Proficiency with frameworks like TensorFlow, Keras, PyTorch, or scikit-learn for implementing machinelearning models.

The ideal candidate will have a passion for solving grid congestion, renewable energy and accelerating the energy transition.

Wij bieden

Emmett Green offers a collaborative and innovative work environment. You’ll be located at our Delft office in Vakwerkhuis with a hybrid work style (some days at the office, some at home). The internship will have a minimum duration of 5 months (start date and duration of internship to be discussed), and we offer a compensation of €500 gross per month.

Max. bestandsgrootte: 64 MB.
Max. bestandsgrootte: 64 MB.

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