This PhD position at Tallinn University of Technology offers an exciting opportunity to advance maritime management in ice-covered marine environments using machine learning and remote sensing. The project is supervised by Full Professor Artu Ellmann (Department of Civil Engineering and Architecture, Road Engineering and Geodesy Research Group) and Assistant Professor Nicole Camille Delpeche-Ellmann (School of Science, Department of Cybernetics, Laboratory of Wave Engineering). The research focuses on developing integrated methodologies for vessel routing in sea-ice environments, combining multi-source sea-level data and harmonizing them to a common vertical datum using geoid modeling. Recent advances in remote sensing (ICESat-2, CryoSat-2, GNSS) and machine learning enable high-resolution measurements and real-time data integration in challenging polar regions. The candidate will develop machine and deep learning models to forecast sea-level variability and sea-ice conditions, improving navigation safety and efficiency for large vessels operating in hazardous Arctic and Baltic waters. The project involves harmonizing datasets from remote sensing, in situ observations, and hydrodynamic models, and validating results through field experiments and statistical analysis. Responsibilities include developing convolutional neural networks and other machine learning techniques, merging sea level, sea ice, and bathymetry data for adaptive routing, and performing sensitivity analyses (RMS error, scatter index, error budgets). The candidate will contribute to related research activities, present findings at scientific workshops, and assist in field campaigns. The research group is actively involved in international collaborations, including the Baltic Sea Chart Datum 2000 and European Space Agency projects, and offers extensive opportunities for conference visits, research stays, and networking with leading universities and research centers. Applicants must have an M.Sc. in geodesy, computing, or a related discipline (Earth Sciences, Marine Engineering, Mathematics, Physics), advanced programming skills (Python, C++, MATLAB), and strong analytical and writing abilities. Beneficial experience includes scientific software, statistics, supervision, and science popularization. The position is a 4-year full-time PhD with additional funds for research training, conferences, and international mobility. Qualified women are encouraged to apply as part of the group’s commitment to increasing diversity in Geomatics and Engineering. To apply, visit the TalTech PhD admission page and submit your CV, motivation letter, degree certificates, research plan, and passport copy to [email protected]. For further information, contact Prof Artu Ellmann. The application deadline is April 1, 2026. The Department of Civil Engineering and Architecture and the Laboratory of Wave Engineering at TalTech are renowned for their interdisciplinary research in geodesy, marine engineering, and coastal management. The research group’s expertise in geoid modeling, GNSS positioning, and wave dynamics provides a strong foundation for this project, which aims to deliver practical solutions for sustainable maritime management in the face of climate-driven environmental change.

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.

This PhD position at Tallinn University of Technology offers an exciting opportunity to advance the prediction of marine extremes using machine and deep learning methods, statistical analysis, and mathematical modeling. The research is situated within the Department of Civil Engineering and Architecture, specifically the Road Engineering and Geodesy Research Group, and is co-supervised by the Laboratory of Wave Engineering in the Department of Cybernetics. The project aims to develop an integrated framework for analyzing and forecasting marine extremes—such as sea level, sea surface temperature, sea ice, and surface waves—across coastal and offshore regions. These predictions are crucial for engineering design, coastal management, and navigation, especially in the context of climate change. The Baltic Sea region provides unique access to long-term, high-resolution marine datasets, including in situ observations, remote sensing products, and hydrodynamic model outputs. By unifying these datasets through a geoid-based vertical reference system, the research will enable consistent and accurate analysis of marine variables. The project emphasizes the integration of data-driven machine and deep learning approaches with mathematical constraints to improve the accuracy, consistency, and predictive skill of marine forecasts. Tasks include harmonizing multi-source datasets, applying statistical methods (such as extreme value analysis), developing convolutional neural network models, investigating links between large-scale climate variability and regional marine processes, and validating model performance using independent data sources and established error metrics. The candidate will be expected to explore and apply machine learning, signal processing, statistical, and computational techniques throughout the project, and participate in field campaigns. The research group is actively involved in international collaborations, such as the Baltic Sea Chart Datum 2000 and European Space Agency projects, and offers a dynamic environment with ongoing European and national research projects. Additional funds are available for research trainings, conferences, and international mobility, with stays abroad of up to three months. Applicants must hold a university degree (M.Sc.) in geodesy or a related discipline (Earth Sciences, Marine Engineering, Mathematics, or Physics). Advanced programming skills (Python, C++, MATLAB), strong writing and analytical abilities, and a good command of English are required. Skills in data analysis, mathematics, statistics, and machine learning are preferred, with training provided as needed. The position encourages applications from qualified women to increase diversity in Geomatics and Engineering. Shortlisted candidates may be asked to submit a research plan. The application deadline is March 24, 2026. To apply, submit your CV, motivation letter, degree certificates, research plan, and passport copy via the TalTech PhD admission portal and email them to [email protected]. For further information, visit TalTech PhD admission and review the supervisors' academic profiles. The research group looks forward to receiving applications from motivated candidates interested in advancing marine prediction science and engineering.