MarDATA 4th Cohort (2026-2029)
Kiel
- Physically informed pattern mining and GNNs for fine scale ocean processes
- AI-derived thermodynamic parameters for aqueous modelling
- Applying inverse reinforcement learning to understand what motivates individual fish movement
Bremerhaven/Bremen
- Network-enhanced feature selection as an enabler of machine learning for eDNA-based ecological assessments of deep-sea ecosystems
- Deciphering Fram Strait’s Organic Matter dynamics from SPECtral high resolution data
***Detailed project descriptions and researcher profiles will follow soon***