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European Doctoral Network Enabling Artificial Intelligence for Electromagnetic Compatibility

Objective

PATTERN is a Doctoral Network at the intersection of electromagnetic compatibility, medical engineering, system-safety engineering, and sustainability management. In its push to go beyond the state of the art the project will embed artificial intelligence (AI) into every challenge. The project will research how best to use AI to discover innovative and sustainable solutions to manage electromagnetic interference (EMI) and develop new sets of design guidelines for electromagnetic reliability and the safety of European medical products of the future.
PATTERNs science case is based on the integration and optimization of every key performance indicator (KPI) linked to the two revolutions faced by medical electronics: risk and sustainability. This requires us to think in terms of a trade-off across a new mix of disciplines, to develop innovative solutions, and to consider all the far-reaching societal and technical consequences of a design choice. Until now, even the most high-tech of industries have been forced to manufacture several prototypes and perform tests, because the actual performance of an EMI solution in a product is unknown. A characterization strategy embedded in these new realities is urgently needed.
PATTERN is the first training network dedicated to the inclusion of AI as the choice of technology to support these paradigm shifts with a new design philosophy. It answers the recently highlighted, pressing need for trained specialists in the field.
PATTERN involves 9 academic Beneficiaries and 9 industrial Associated Partners, across the complete lifecycle of design solutions, from 8 countries. A pan-European approach in a multi-sectoral context is guaranteed (universities, an established start-up, SMEs, and major industries)
PATTERN will train a new generation of scientific professionals who can transition between disciplines and take up leading positions in the field of electronics, safety, sustainability and AI, while thinking about design differently.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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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)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

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-2023-DN-01

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Coordinator

TECHNISCHE UNIVERSITEIT EINDHOVEN
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.

€ 1 097 481,60
Address
GROENE LOPER 3
5612 AE Eindhoven
Netherlands

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Region
Zuid-Nederland Noord-Brabant Zuidoost-Noord-Brabant
Activity type
Higher or Secondary Education Establishments
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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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Participants (7)

Partners (12)

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