Objective
Accelerating Europe’s green and digital transitions requires advanced tools capable of modelling and optimising the complex reactive flows that underpin clean energy systems, propulsion technologies, and fire-safety applications. Yet current simulation approaches remain too computationally demanding to capture the multi-physics behaviour of low- and zero-carbon fuels such as hydrogen, ammonia, and e-fuels, which are essential for decarbonising hard-to-electrify sectors. ASCEND addresses this challenge by delivering the next-generation fully integrated modelling framework that leverages artificial intelligence (AI) and high-performance computing (HPC) technologies to accelerate reactive Computational Fluid Dynamics (CFD) simulations. By enabling order-of-magnitude reductions in computational cost while preserving physical fidelity, ASCEND will set a new European benchmark for predictive, fuel-flexible simulation tools.
ASCEND will train 12 Doctoral Candidates to become a new generation of experts at the interface of combustion science, scientific machine learning (SciML), and high-performance computing. Bringing together six leading European universities and research centres, supported by a diverse group of industrial and academic associated partners, the programme offers interdisciplinary training in physics-informed ML, uncertainty quantification, GPU-aware numerical methods, and computational fluid dynamics. This will equip researchers with the cutting-edge skills needed to design fast, trustworthy, and scalable digital tools.
By developing physics-informed, hardware-accelerated ML frameworks that drastically reduce computational cost while maintaining high physical fidelity, ASCEND will strengthen Europe’s scientific leadership, accelerate innovation in clean energy technologies, and contribute to a highly skilled workforce vital for achieving EU climate, digital, and sustainability objectives.
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.
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.
- social sciences economics and business business and management employment
- natural sciences computer and information sciences computational science multiphysics
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences mathematics applied mathematics numerical analysis
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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)
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.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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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.
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.
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.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-DN-01
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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.
E1 4NS LONDON
United Kingdom
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Participants (5)
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64289 Darmstadt
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9000 Gent
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38106 Braunschweig
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EH8 9YL Edinburgh
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08034 BARCELONA
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Partners (9)
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SE1 7NA London
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LN5 7FD LINCOLN
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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1930 Zaventem
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141 74 Stockholm
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52428 JULICH
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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8092 Zuerich
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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75794 Paris
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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27695 7514 Raleigh
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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08034 BARCELONA
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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.