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Autonomous Scanning Probe Microscopy for Life Sciences and Medicine powered by Artificial Intelligence

Objective

Artificial Intelligence is pushing forward the Industrial Revolution 4.0 which is transforming many areas of Society, including Science and Technology. Nanoscopy, a recognized pillar of the research and manufacture of Nanotechnology-based products, is among the areas that more quickly is adopting Artificial Intelligence. Machine learning algorithms are being developed and integrated in microscopes for its autonomous operation and in software toolboxes for the automatic analysis of large volumes of microscopy data. Scanning Probe Microscopy is particularly active in this integration with a special focus in the Life Sciences and Medical fields. Scanning probe microscopes powered by machine learning are expected to enable the autonomous and label-free nanoscale structural and functional (mechanical and electric) imaging of living cells and functional biomolecules in their native conditions, something never achieved in nanoscopic imaging. The objective of the SPM4.0 Doctoral Network is to train a new generation of researchers in the science and technology of autonomous Scanning Probe Microscopes powered by Artificial Intelligence for applications in the Life Science and Medical fields. The researchers of the network will acquire a state-of-the-art multidisciplinary scientific training in advanced scanning probe microscopy and machine learning and in their biological and medical applications. In addition, they will receive training on complementary and transferable skills to increase their employability perspectives and to qualify them to access to responsibility job positions in the private and public sectors. The final aim is to promote the wide adoption of SPM4.0 technologies in public and private research centers and in industrial and metrology institutions and to explore new horizons in the Life Sciences and Medical sectors regarding label-free nanoscopic cell imaging, illness diagnosis, or drug nanocarrier development, consolidating Europe as world leader.

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

FUNDACIO INSTITUT DE BIOENGINYERIA DE CATALUNYA
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.

€ 755 913,60
Address
CARRER BALDIRI REIXAC PLANTA 2A 10-12
08028 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
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 (11)

Partners (10)

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