Awarded Projects

This project is concerned with the general problem of nano-pollutant removal. The final objective is to provide a reliable framework for the study of aggregation and removal of suspended solids by means of Nanobubbles.

This proposal develops an AI-driven, multi-pollutant model for operational regional air-quality forecasting over Europe, implemented within ECMWF’s Anemoi framework.

Contact line phenomena entail multi-physics processes that operate at disparate scales, often posing formidable large-scale computing challenges.

DigiFarm is one of Norway's leading ag-tech startups, established in 2019 who's core focus is on developing deep neural network models in agriculture leveraging SatEO data.

Numerical weather prediction (NWP) plays a critical role for European societies to avoid weather-induced harm and improve benefits, e.g. in the agricultural sector or for renewable energies.

Accurate medium-range weather prediction is of critical importance for European societies to prevent weather-induced loss of life and economic damages.

The study will couple committee-based active learning with synthetic nanoreactor simulations that drive QD surfaces into reactive, high-uncertainty regimes and trigger on-the-fly DFT relabelling.

This project focuses on developing AI-assisted features for the WebRatio low-code platform by fine-tuning a Large Language Model (LLM) to generate IFML models in XML format, leveraging WebRatio's proprietary codebase.

Thermodynamic modelling routinely guides the research and development (R&D) of new materials and the CALPHAD (CALculation of PHAse Diagrams) method is one of the approaches of choice because of its accuracy achieved with a modest computational effort.