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Neuromorphic computing and signal processing training network

Objective

The exponential surge in artificial intelligence (AI), internet traffic, and online services demands a revolutionary leap in devices, computing architecture, and integration technologies. Current digital computing platforms, driving societal progress, are hitting fundamental limits such as quantum tunneling and facing technical challenges like energy efficiency and heat dissipation. As a result, the progress in AI is slowed down by speed bottlenecks, massive energy consumption, and limited access to AI technologies as only selected large industrial players can afford to commit the required resources. Inspired by the brain’s powerful and energy-efficient processing capabilities, neuromorphic computing presents a promising solution to these critical issues. However, to fully harness neuromorphic computing’s potential, a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across multiple technological platforms - photonics, electronics, biological neurons - is critically needed. The proposal of MINDnet addresses these urgent challenges through an interdisciplinary approach, bridging traditionally separate fields. MINDnet’s mission is to train 15 Doctoral Candidates, forming the next generation of leading scientists and expert researchers in the field of neuromorphic computing. MINDnet leans on a consortium of 10 beneficiaries - 7 universities, 1 tech-transfer research center, 1 multinational, 1 SME - complemented by 6 associated partners – 1 multinational, 2 SMEs, 2 tech-transfer research centers, and 1 academic. The consortium spans over 8 European countries, combining experts in 5 research disciplines - photonics (DTU, UNITN, USTRATH), electronics (UCL, HPE, FZJ, SCS), nonlinear dynamics (TUIL) and machine learning (UNIPI, TUG), - as well as a strong focus on the 5 applications - telecom (NVIDIA, HHI), sensing (FCAP), geolocation (AT), space (NB), and biomedical (UNITN).

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

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-DN - HORIZON TMA MSCA Doctoral Networks

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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-2024-DN-01

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Coordinator

DANMARKS TEKNISKE UNIVERSITET
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.

€ 671 780,16
Address
ANKER ENGELUNDS VEJ 101
2800 KONGENS LYNGBY
Denmark

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Region
Danmark Hovedstaden Københavns omegn
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.

No data

Participants (9)

Partners (6)

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