A new PhD position in Drone-based Terrestrial Snow Monitoring is currently open on Svalbard, offering an exciting opportunity to work on Arctic remote sensing research.
Based in Longyearbyen, Svalbard, with Larissa Beumer the position focuses on advancing high-resolution snow monitoring using drone-based approaches. The project aims to bridge a critical gap in current snow observation capabilities: while satellite data provide large-scale coverage, they often lack the spatial and temporal resolution needed for ecological and geophysical applications. By integrating drone data with in situ measurements and satellite products, the PhD candidate will contribute to developing new methods for capturing snow properties such as depth, distribution, and related parameters at unprecedented detail.
The research is embedded within a highly interdisciplinary Arctic research environment and closely connected to ongoing monitoring efforts such as the COAT (Climate-ecological Observatory for Arctic Tundra) network. Fieldwork in Svalbard will be an integral part of the project, alongside geospatial analysis, modelling, and collaboration with international partners.
This position is also strongly linked to our EORC. Tobias Ullmann is part of the PhD committee, supervision further includes Mirjana Bevanda and Jakob Schwalb-Willmann, both of whom contributed to the original project proposal together with Larissa Beumer and colleagues at UNIS. This highlights the collaborative and international nature of the project from its inception.
The successful candidate will join the Department of Arctic Biology at UNIS and will be enrolled in a PhD programme in Norway. The position offers a unique chance to conduct cutting-edge research in a rapidly changing Arctic environment, contributing to improved understanding of snow dynamics and their implications for ecosystems, permafrost, and climate processes.
The application deadline is 7 April 2026. Further details and application instructions are available via the official job posting:
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This PhD represents an excellent opportunity for candidates interested in drone-based remote sensing, Arctic research, and interdisciplinary environmental science.
