An event that explores the highly demanded field of Data Science in modern society, and creates links with the industry
The conference will take place from 8 to 10 June, 2026, in Santiago de Compostela (Galicia, Spain)
REGISTRATION OPEN!
Registration fees: School + Symposium: 150€ | Symposium: 75€
School (8-10 June): Intensive course on Probability, Statistics, Machine Learning and Complexity, focused on PhD students and postdoctoral research staff. The sessions will be led by Glen Cowan (Professor of Physics at the Royal Holloway in London) and Eddie Lee (researcher at the Complexity Science Hub in Vienna).
Symposium (11-12 June): The school will be followed by a symposium focusing on the relationship between fundamental physics and industry, with data science as the nexus.
Confirmed companies: Anaxa, Bahia Software, CESGA, Clarity AI, Finsa, ITG, FSAS - Fujitsu, Google, Gradiant, Inditex, ITG, Mestrelab, Navantia, Novartis, Plexus Tech, Quantum Spain, SDG Group.
During these days, more than 20 representatives from companies and research centres will discuss and share knowledge about the latest trends in the sector, the demands, and practical applications of data science in everyday life.
The event aims to demonstrate the career opportunities within fundamental physics and its synergies with the job market and modern society’s needs. It will include a school covering Data Science techniques used in High Energy Physics (HEP), Nuclear, Astroparticle, and Fundamental Physics, alongside a symposium where companies present their current trends, needs, and daily work related to Data Science.
Additionally, the event intends to establish communication channels with the industry to explore partnerships, joint projects, and international grant opportunities. It will also highlight IGFAE’s research capabilities in Nuclear, High Energy, AstroParticle, and Fundamental Physics in the field of Data Science. By bringing together both sides, this event will create a framework for mutual knowledge exchange and enable the development of practical synergies from Data Science in fundamental physics to Data Science in the industry.
