FPI Predoctoral Fellowship

Why IE University?

Every story begins with a purpose, and ours has always been about people. Founded in 1973, IE University has continuously raised the bar to drive positive change through education. We believe education is more than a path to professional success; it is a catalyst for personal transformation and meaningful impact. 

At IE University, we place people and their potential at the center of everything we do, empowering individuals to become extraordinary. We encourage bold thinking and foster a culture where innovation, curiosity, and courage lead to real-world impact. Together, we create an environment where talent thrives, and ideas shape the future. 

Our mission 

We support students in developing impact skills to live and lead with positive impact. This ignites a ripple effect: We transform people, who then transform others, systems, society, and, ultimately, our world.  

Our Purpose

To foster positive change.  

Values  

1. Cultivate the humanistic approach.  
2. Empower your entrepreneurial spirit 
3. Cherish the diversity of people, mind, and experience 
4. Drive innovation with a proactive mindset

PhD Predoctoral Fellowship to join the KAN4Met project and develop next‑generation AI weather forecasting models based on Kolmogorov–Arnold Networks (KANs). The research will combine deep learning, atmospheric data and HPC.

We offer a fully funded FPI PhD position in the project “Kolmogorov‑Arnold Networks with applications in weather forecasting (KAN4Met)”, led by Prof. David Gómez‑Ullate. https://ieresearchdatalab.github.io/KAN4Met/ The PhD candidate will join an interdisciplinary team of mathematicians, physicists, statisticians and computer scientists working at the intersection of approximation theory, AI and atmospheric science. The goal is to understand and improve KAN architecture and to develop an AI weather prediction model for the Iberian Peninsula, inspired by the latest advances in AI forecasting.

The candidate will have the opportunity to complete one or more 3‑month international research stays in top research institutions, gaining exposure, collaborations and a broader scientific perspective.

• RESEARCHER PROFILE: Master
• Required Education level: MSc/MEng in Mathematics, Physics, Computer Science or Engineering
• Research field:Computer Science / Applied Mathematics / Data Science / Engineering
• Required Languages: English (B2 requiered, C1 desirable)
• Knowledge of deep learning frameworks, Neural ODEs, Physics‑Informed Neural Networks, and High‑Performance Computing will be valued.
• Academic record, research merits and motivation to pursue a PhD will be the main criteria. The process will be based on the applicant’s CV, motivation letter and an interview.