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Machine learning for Sciences and Humanities

Project description

Human researchers trained in machine learning

Researchers in Slovenia will receive training in machine learning applications. The Marie Skłodowska-Curie Actions are supporting the launch of the SMASH project, which comprises a training and research programme (co-funded by the Slovenian Ministry of Science, Education and Sport). The programme is designed to enhance the career prospects of outstanding postdocs from around the world while strengthening Europe's human capital in the field of research and innovation. SMASH will use innovative data science to delve into some of the world’s most challenging issues. These include predictions related to the impacts of climate change, the development of personalised medicine, finding answers to fundamental questions about our universe and digging deep into the fundamentals of language and how we communicate.

Objective

SMASH is a brand-new training and research programme to be co-funded by the Slovenian Ministry of Science, Education & Sport. The Beneficiary, the University of Nova Gorica, is a research-focused university, situated at the Italian border, that boasts a 51:49 female:male ratio among its 200+ staff. The programme is designed to enhance the career prospects of outstanding post-docs from around the world, while strengthening Europe's human capital in R&I.
Fifty talented individuals will be hired by five of Slovenia’s leading institutions, allowing them to expand their own research ideas based on access to the data-science potential of the Vega HPC supercomputer, the first such facility of the EU’s €-multi-billion HPC initiative. With a diverse group of Associated Partners, including top SMEs from Slovenia and the EU as well as world-leading institutions like UC Berkeley, SMASH will form a close-knit community with a single unifying concept: the use of cutting-edge data science to answer some of the world’s most challenging questions. These include predictions related to the impacts of climate change, the development of personalised medicine, finding answers to fundamental questions about our Universe and digging deep into the fundamentals of language and how we communicate.
SMASH will guarantee a recruitment process based on openness, transparency, impartiality and equality, and will ensure neutrality by giving all selection power to external experts, setting an example for the region. Top-level training in applications of machine learning, that is one of today’s most transferable skills, will be complemented by rich soft-skill training opportunities, developed in collaboration with some of the world’s best experts, including CERN's Learning Hub. The impact of the programme will be felt for decades, both in the local research landscape and across Europe as the researchers take their skills to pursue their careers on the strength of their successes in SMASH.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-TMA-MSCA-Cofund-P - HORIZON TMA MSCA Cofund Postdoctoral programme

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-MSCA-2021-COFUND-01

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Coordinator

UNIVERZA V NOVI GORICI
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 4 776 000,00
Address
VIPAVSKA CESTA 13 ROZNA DOLINA
5000 Nova Gorica
Slovenia

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Region
Slovenija Zahodna Slovenija Goriška
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Partners (31)

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