AI-Based Surrogate Modelling of Marine Environment in the Baltic Sea Tallinn University of Technology in Estonia

TalTech (Tallinn University of Technology) is offering a fully funded PhD position on AI-Based Surrogate Modelling of Marine Environment in the Baltic Sea. The project sits at the interface of marine science, computational science, and artificial intelligence, and is part of the newly established AIMES project funded by the Estonian Research Council.

The PhD research aims to develop AI-based emulators for key Baltic Sea oceanographic processes, including circulation, tracer transport, heat evolution, biogeochemistry, and ecology. The work will focus on harmonising multi-source marine datasets, identifying important process drivers, and building deep learning models for spatiotemporal prediction. The candidate will explore advanced architectures such as convolutional, recurrent, graph-based, transformer, and neural-operator models, with an emphasis on physics-informed machine learning, uncertainty-aware prediction, and computational efficiency.

This position is especially relevant for candidates interested in scientific machine learning, computational oceanography, and large-scale environmental data analysis. The research will be carried out within the Modelling and Remote Sensing of Marine Dynamics team at the Department of Marine Systems, an internationally active group working on marine science, remote sensing, operational forecasting, and AI. The team uses high-performance computing, numerical models, satellite observations, and large environmental datasets to study atmosphere–ocean interactions and marine environmental change.

The advertised role is a fully funded fixed-term 4-year PhD Early-stage researcher position with a gross monthly salary of 2300 euros. Additional support includes access to computational infrastructure, high-value datasets, collaborative research networks, conference participation, research visits, international collaboration, and training in reproducible workflows, scientific writing, and science communication.

Applicants should hold a relevant Master’s degree and demonstrate strong academic performance. A background in computer engineering, computational science, data science, artificial intelligence, applied mathematics, oceanography, or atmospheric science is suitable. Programming skills, preferably in Python, and familiarity with Linux, PyTorch, and HPC environments are expected. Strong English, motivation to publish, and ability to work both independently and in an interdisciplinary team are important.

The application window is 14.08.2026 to 13.09.2026. The position is based at Tallinn University of Technology in Estonia.