Loading…
Loading grant details…
| Funder | European Commission |
|---|---|
| Recipient Organization | Universite de Strasbourg |
| Country | France |
| Start Date | Feb 01, 2024 |
| End Date | Jan 31, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 10 |
| Roles | Associated Partner; Coordinator; Participant |
| Data Source | European Commission |
| Grant ID | 101120240 |
The Marie Skodowska-Curie Doctoral Network ""ML4Q - Machine Learning for Quantum"" provides high-level interdisciplinary, intersectoral and international training to 10 doctoral researchers who will explore how machine learning and quantum science technology can be combined to (i) extend quantum and classical machine learning based prediction of materials and matter properties and to strongly-correlated regimes, and (ii) accelerate the development of quantum technologies through machine learning, thus enabling new approaches to solving outstanding problems currently out of reach of classical computers.
This has the potential to address some of the world's most pressing challenges, such as developing tools for discovering more environmentally friendly chemical processes and efficient materials, or accelerating the development of quantum technologies which will give Europe an edge in the global tech race.
ML4Q fellows will realize this vision will through their individual projects and interdisciplinary collaborations reinforced by a comprehensive training program which combines cutting-edge research with a focus on networking, career development for academic and non-academic career paths, open science and responsible research and innovation for society, that will enable them to shape emerging technologies and the next digital transformation in Europe.
The consortium consists of 5 academic and 5 non-academic research partners (including 2 leading Eu QT startups) and 11 principal investigators who bring together all the necessary expertise computer science, AI and machine learning, quantum technology, and chemistry and materials science, as well as their interfaces.
Together we will prepare the next generation of strong, resilient, flexible, and creative quantum and computer scientists with the combination of skills needed to meet the future needs of the rapidly evolving innovative materials, quantum technologies industries, as well as other knowledge based sectors.
Sick Ag; Universite de Strasbourg; Quantfi Sas; Universita Degli Studi Di Padova; Consiglio Nazionale Delle Ricerche; Karlsruher Institut Fuer Technologie; Eotvos Lorand Tudomanyegyetem; Qruise Gmbh; Universita Degli Studi Di Modena E Reggio Emilia; Leitha Srl
Complete our application form to express your interest and we'll guide you through the process.
Apply for This Grant