SCIANCE is gathering evidence on scientific challenges, AI capabilities, infrastructures and emerging practices in “AI in Life Sciences”, supporting the identification of strategic priorities for RAISE.
Resources
Explore resources about AI-enabled scientific research in Europe
AI for Data Science & Advanced Analytics
SCIANCE is gathering evidence on scientific challenges, AI capabilities, infrastructures and emerging practices in “AI for Data Science & Advanced Analytics”, supporting the identification of strategic priorities for RAISE.
SuperCode
AI-assisted optimisation of scientific software for sustainable computing
WorldCereal
Open, retrainable crop-mapping workflows with emerging foundation-model integration
YieldSAT
A multimodal benchmark dataset for field and subfield crop yield prediction
Tessera
Open reuse of geospatial foundation-model embeddings for Earth observation
Semantic workflows for atomistic simulations
Toward Knowledge-Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties
Bonding Analysis Database and Machine Learning Framework
Ontology-Aligned Materials Workflows
Ontology-Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction
Deep Learning for Slurry Modelling
Deep learning-enhanced physical modelling for tape-casting slurry microstructures of solid oxide cell substrates
polySCOUT
Deep learning-enhanced physical modelling for tape-casting slurry microstructures of solid oxide cell substrates
pyMarAI
Human-in-the-Loop Deep-Learning Toolchain for Tumor Spheroid Delineation