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Artu Ellmann

8 months ago

PhD Position in Machine and Deep Learning for Marine Extremes Prediction in Engineering and Navigation Tallinn University of Technology in Estonia

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Estonia

University

Tallinn University of Technology

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Keywords

Computer Science
Machine Learning
Environmental Science
Deep Learning
Remote Sensing
Mathematics
Statistical Analysis
Geography
Hydrology
Civil Engineering
Architecture
Earth Science
Geodesy
Sea Level
Data Harmonization
Statistics
Climate Variability
Sea Ice
Convolutional Neural Network
Physics

About this position

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.

Funding details

Available

What's required

Applicants must hold a university degree (M.Sc.) in geodesy or a closely related discipline such as Earth Sciences, Marine Engineering, Mathematics, or Physics. Advanced computer literacy and programming skills (e.g., Python, C++, MATLAB) are required. Strong writing and analytical skills are expected. Skills in data analysis, mathematics, statistics, and machine learning methods are preferred (training will be provided if needed). Candidates should demonstrate the ability to conduct independent research as part of a team and have an interest in presenting and publishing scientific results. Good command of English (speaking and writing) is required. Shortlisted candidates may be asked to submit a research plan for the topic.

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Professors

Full Professor at Tallinn University of Technology

University Name
Country flag

Estonia

Research Interests

Statistics

Oceanography

Sea Level

Geodesy

Physics

Assistant Professor at Tallinn University of Technology

University Name
Country flag

Estonia

Research Interests

Statistics

Hydrology

Machine Learning

Computer Science

Deep Learning