SMASH tackles the most complex research challenges with the help of AI
Ljubljana, 23 September - The University of Nova Gorica is in charge of a European project featuring four other Slovenian partners aimed at developing cutting-edge machine learning applications to take on some of the toughest challenges in data science, space research, medicine, linguistics and climate research.
In cooperation with the University of Ljubljana, the Jožef Stefan Institute, the National Environment Agency and the Maribor Institute of Information Science, the University of Nova Gorica obtained the COFUND SMASH project worth 10 million Euros, which is co-financed by the Horizon Europe research and innovation programme.
The first COFUND project coordinated by a Slovenian organization involves 32 associate partners, including some of the most innovative Slovenian businesses and prestigious academic institutions abroad, such as CERN in Geneva and the University of California in Berkeley.
The goal over the next five years is to attract 50 postdoctoral researchers from all over the world, including Slovenian researchers who work abroad. Eight fellows have already been selected, and the second phase of the call for applications is open until 27 October.
They will be offered a two-year fellowship at one of the five host institutions in Slovenia, and the opportunity for secondments, including at associate partners in Europe, the US, Brazil, South Africa and Israel.
Their research will be based on machine learning methods and artificial intelligence and carried out with the help of the Vega supercomputer, with the aim to find solutions to some of the most complex challenges in five areas: data science, particle physics, astrophysics and cosmology physics, linguistics, climate, and precision medicine.
Gabrijela Zaharijaš, the project's coordinator, sees SMASH as a great opportunity to bring brilliant scientists and new knowledge in this emerging field to Slovenia.
The head of the Physics PhD programme at the University of Nova Gorica and researcher at the university's Centre for Astrophysics and Cosmology, Zaharijaš hopes that the project will strengthen cooperation between AI and other scientific fields to help enable new and surprising discoveries.
Out of the 50 participants, the projects aims to attract at least 40% of women researchers or researchers from other under-represented groups, said Andreja Gomboc, a researcher at the Centre for Astrophysics and Cosmology who supervises the project.
"Diversity, equality and inclusion are among the project's priorities, and so the evaluation process is structured to minimise unconscious bias. For example, the first stage of evaluation will be double-blind, meaning that evaluators will not know who the authors of proposed research projects are or from which country or institution they come," she said.
In the SMASH project, Gomboc focuses on the application of machine learning methods in astronomy and cosmology in collaboration with the Vera C. Rubin Observatory in Chile and its LSST project.
Researchers in this field will be given access to a huge database as part of the LSST project, which will acquire about 40 terabytes of data per night or about 60 petabytes over ten years, she added.
According to Iain White, another SMASH project supervisor and researcher at the university, the selected fellows can count on not just opportunities for research but also career development, since the project includes soft skills courses on topics such as leadership, applications for funding, and ethics in science.