PhD Position in Machine and Deep Learning Methods to Understand and Predict Sea Ice Changes Using Remote Sensing Techniques Tallinn University of Technology in Estonia

This PhD position at Tallinn University of Technology offers an exciting opportunity to advance the understanding and prediction of sea ice changes in the Baltic and Barents Seas using state-of-the-art machine and deep learning methods. The research is situated within the Laboratory of Wave Engineering, part of the Department of Cybernetics, School of Science, and supervised by Assistant Professor Nicole Camille Delpeche-Ellmann and Tenured Full Professor Dr. Tarmo Soomere. The laboratory is renowned for its expertise in wave dynamics, coastal engineering, and the application of mathematical and computational methods to marine environments.

Climate change is driving rapid alterations in sea-ice properties and dynamics, with significant implications for marine engineering, coastal management, and navigation. The project leverages long-term, high-resolution datasets from the Baltic Sea, including in-situ measurements, satellite products (ICESat-2, CryoSat-2), and hydrodynamic models. The successful candidate will develop an integrated framework combining remote sensing, in situ observations, and hydrodynamic model outputs to analyze and forecast sea ice changes. The methodology will be applied to both the Baltic and Barents Seas, focusing on the marginal ice zone (MIZ), a region undergoing rapid transformation due to complex interactions among sea ice, ocean, atmosphere, waves, and currents.

The PhD candidate will harmonize multi-source datasets onto common spatial and temporal scales, apply statistical methods such as empirical orthogonal functions, wavelet transform, and extreme value analysis to identify patterns and trends in sea ice extent, thickness, and velocity. Machine and deep learning models, including convolutional neural networks, will be developed to reconstruct past, present, and future scenarios and quantify associated uncertainties. The research will also investigate links between large-scale climate variability and regional-to-local marine processes, examining how sea ice changes influence energy, momentum, and carbon exchanges using Earth system models (e.g., CMIP6).

Applicants should hold a master’s degree or equivalent in Earth sciences, computing, or related disciplines such as marine engineering, mathematics, geodesy, or physics. Advanced programming skills (Python, C++, MATLAB), strong analytical and writing abilities, and a clear interest in the research topic are essential. Experience with scientific software, statistics, and machine learning methods is beneficial, and training will be provided as needed. Good command of English is required, and shortlisted candidates may be asked to submit a research plan.

The position is fully funded for four years, offering tuition and stipend, and provides extensive opportunities for conference visits, research stays, and networking with leading universities and research centers in coastal and ocean engineering. The laboratory is highly internationalized and actively engaged in pan-European and national research projects. Hands-on training in science communication and diplomacy is also available.

To apply, candidates should review the PhD admission information at TalTech’s web page and submit their application documents (CV, motivation letter, degree certificates, research plan, and passport copy) to [email protected]. For further information, visit the laboratory website.

This position is ideal for candidates passionate about climate science, marine engineering, and computational methods, seeking to contribute to impactful research in a dynamic and supportive environment.