Opening date-15 February 2025
Deadline date-14 April 2025 17:00 (Brussels time)
Expected duration of participation– 3-6 months (Project execution timeframe: 1 July 2025 – 31 May 2026)
TYPE OF BENEFICIARY
- PhD candidates (who demonstrate their enrolment in a PhD programme)
- Post-docs (who demonstrate their employment at a university, research centre or business entity)
- Senior researchers (who demonstrate their employment at a university, research centre or business entity)
In case of a group of researchers applying the team needs to be composed by a one PhD candidate + one Post-doc/Senior Researcher.
Researchers from ENFIELD partner organisations are not eligible to apply.
ELIGIBLE COUNTRIES
Applicants eligible to receive funding through this Open Call are researchers based in EU Member States or Horizon Europe associated countries only.
APPLICATION PROCESS
The application process is described in more detail in the Guide for Applicants available at https://www.enfield-project.eu/oc3_TES_2025.
Project proposals must be submitted by completing the application online, here: https://ec.europa.eu/eusurvey/runner/oc3-2025-TES-01.
It is strongly recommended not to wait until the last minute to submit the proposal. Failure of the proposal to arrive in time for any reason, including network communications delays or working from multiple browsers or multiple browser windows, is not acceptable as an extenuating circumstance. Late submissions are not permitted. The time of receipt of the application as recorded by the submission system will be definitive.
Proposals must include a Technical Annex. The template can be found here: https://www.enfield-project.eu/oc3_TES_2025.
Proposals must include a 2-minute video from the applicant presenting themself (or the group of researchers), submitted in English.
PROPOSAL EVALUATION
The evaluation will be done remotely by three senior researchers from ENFIELD partners’ scientific organisations.
The proposals will be scored (between 0- fail and 5- excellent) based on the criteria below:
1) Advanced state of the art: The extent to which the proposal is beyond the state-of-the- art and presents an innovative approach behind it (e.g., novel concepts and methodologies, development between or across disciplines, novel methods and algorithms addressing societal challenges).
2) Scientific approach: Feasibility of the proposed research methodology and working arrangements.
3) Dissemination and communication: Effectiveness of the proposed measures to exploit and disseminate the project results which must include methods (publications, presentations, workshops and/or webinars) and targeted audiences.
4) Technical and creative capacities: i) Demonstration of competences and skills of the researcher (or group of researchers) involved in the proposal. ii) Ability to carry out the activities for the proposed application. iii) Track-record of the team in scientific publications and similar projects. In case of an application submitted by a consortium, complementarity of researchers.
ENFIELD Exchange Open Calls does not fund research itself but promotes interactions and strengthens research collaboration among researchers across Europe by granting employed researchers (PhDs, postdocs, senior researchers) with a mobility allowance of 2.400€/month (up to 14.400€ in total) for them to carry out research activities in ENFIELD partner organizations for 3-6 months.
Details are available at: https://www.enfield-project.eu/oc3_TES_2025
Task description
Grants to conduct foundational research activities related to specific scientific/technological challenges in artificial intelligence:
Green AI
G-AI.1 Green AI Metrics
G-AI.2 Physics-Informed Machine Learning
G-AI.3 The Policy Landscape for Green AI
G-AI.4 Green Generative Language Models
G-AI.5 Energy-Efficient Large Language Models for Sustainable Software Engineering
G-AI.6 Green World Models
G-AI.7 Cooperative Multi-agent Green AI
Adaptative-AI
A-AI.1 Adaptive AI for Environmental Monitoring: Multimodal Data Fusion for Context Aware Deployment
A-AI.2 Adaptive AI for Multimedia: Learned Compression and Real-Time Applications
A-AI.3 Adaptive AI on the Edge – Innovations for Resource-Constrained Systems
A-AI.4 LLM on the Edge
A-AI.5 Adaptive AI-Powered Digital Twin for Innovating Healthcare Security and Resilience
A-AI.6 Adaptive AI for Generalizable and Multimodal Semantic Reasoning
A-AI.7 Zero-shot large-scale biomedical entity matching and linking
A-AI.8 Parameter Efficient Algorithms for Foundation models
A-AI.9 Robustness and Generalization in single or multi-modal models
Human-Centric AI
HC-AI.1 Interpretability and uncertainty in predictive models
HC-AI.2 Improving transparency and explainability of web-based AI systems through semi-structured natural language descriptions
HC-AI.3 Explainable AI for Multimodal and Sequential Data Analysis in Physical and Chemical Processes.
Trustworthy AI
T-AI.1 Security and Robustness of AI systems
T-AI.2 Privacy and Compliance of AI systems
T-AI.3 Trustworthy ML based scheduling for the energy domain
T-AI.4 AI in Distributed Systems
T-AI.5 Assessing Trustworthiness of Distributed AI Systems
T-AI.6 Brain-to-Speech Interface: From Neural Signals to Communication Restoration
T-AI.7 Secure Voice Biometrics with Fake Voice Detection
Energy
VE.1 Combine AI with LLM for clear human interaction with complex data
VE.2 LLM based data queries and visualization
Space
VS.1 Synthetic dataset generation of foreign object debris on runways and FATOs
VS.2 Detection of potential water illegal abstractions using Artificial Intelligence and Earth Observation
VS.3 Causal Machine Learning model to identify agricultural practices aiding in yield productivity improvement using Earth Observation (EO) data
Manufacturing
VM.1 Context-agnostic Computer Vision human detection
VM.2 Machine Learning-based stress detection for human operators