Call for Fellows

Earth Observation: full-grant fellowships available

Pi School is looking for candidate fellows for the Pi School of AI 8-week programme starting on January 16th 2023, who are already familiar with the Earth Observation (EO) context.

Earth Observation: full-grant fellowships available
Photo by NASA on Unsplash

At a glance

  • START DATE January 16th, 2023
  • DURATION 8 weeks full-time
  • LOCATION 6 weeks remotely + 2 weeks in Rome
  • FEES The programme fees of 12,500 € are fully covered by the available grants.
Apply now!

The Pi School of AI is a leading international school promoting innovation, creativity and entrepreneurship. We are committed to continual learning and training talents that will reshape our future. Since 2017, we have welcomed hundreds of up-and-coming AI engineers and challenged them to solve industry problems in healthcare, energy, space, finance, and sustainability, among others.

In Session 12 of Pi School of AI, we will work on a challenge in the context of the SeasFire project, which deals with “Earth System Deep Learning for Seasonal Fire Forecasting” in collaboration with the National Observatory of Athens (NOA) and the support of ESA Φ-lab.

To be admitted to the Pi School of AI programme, candidates must already have exposure to Python Data Science Stack (NumPy, Pandas, Scikit-learn, etc.) with a focus on Deep Learning (Pytorch or Tensorflow).

Particularly for this challenge, applicants must be confident with the EO Python Stack (e.g. xarray, geopandas). In addition, during the selection process, we will consider a familiarity with Graph Neural Networks (PyTorch geometric, PyTorch geometric temporal) and transformed-based architectures as assets.

As the challenge may involve Time Series Forecasting, causality, and explainability methods, these skills will be considered optional assets.

You’ll be mentored by some of the finest minds, representing institutions such as Cambridge, Google, Facebook, Amazon, Carnegie Mellon and more. All while gaining hands-on AI and Machine Learning experience and specialist skills by working on your sponsor company’s industry project.