Observing Whitecapping-Driven Wave Dissipation in Coastal Ocean with Synthetic Aperture Radar Tallinn University of Technology in Estonia

PhD/Early-Stage Researcher opportunity at Tallinn University of Technology in coastal ocean remote sensing and machine learning.

This project, Observing Whitecapping-Driven Wave Dissipation in Coastal Ocean with Synthetic Aperture Radar, focuses on how wave breaking and whitecapping control air–sea momentum exchange, gas transfer, upper-ocean turbulence, and energy dissipation in coastal waters. The research will use Sentinel-1 and other C-/X-band SAR data together with wave-buoy spectra, meteorological forcing, and available in situ observations such as ADCP or echosounder measurements. The aim is to develop and test methods for estimating whitecapping-related dissipation from SAR, build robust proxies, and determine when and where SAR can reliably constrain breaking-related energy loss in the Baltic Sea.

The methodological core combines empirical, machine-learning, and physics-informed approaches. The doctoral researcher will assemble and quality-control multi-sensor datasets, retrieve breaking-sensitive metrics from SAR imagery, link them to sea-state descriptors and collocated wave spectra, and quantify uncertainty and sensitivity to wind sea versus swell, incidence angle, viewing geometry, rain, sea-state maturity, and wind–wave misalignment. The thesis will also compare retrievals with model data and assess spatial and temporal limits for robust dissipation estimation in the Baltic Sea.

The position sits within the Department of Marine Systems at TalTech, a major Baltic Sea oceanographic and meteorological R&D unit with strong expertise in operational oceanography, satellite and model data analysis, and marine monitoring services. The broader environment includes work contributing to Copernicus Marine Service (CMEMS) and Destination Earth (DestinE), offering a strong setting for research in satellite data processing, coastal oceanography, and machine learning.

This is a 4-year full-time fully funded PhD position. The university also notes opportunities to engage in applied projects funded by the European Commission and the European Space Agency, as well as conference visits, research stays, and networking with international universities and research centres.

Eligibility highlights: a Master’s degree in Natural Sciences or Engineering (preferably oceanography, physics, geophysics, remote sensing, data science, applied mathematics, or a related area), good programming skills, preferably in Python, strong English, and demonstrated writing and analytical ability. Experience with MATLAB or R, Linux/Unix, reproducible workflows, HPC, Copernicus or similar data services, and geospatial or environmental datasets is advantageous.

Application window: 14 August 2026 to 13 September 2026.