PhD in Forest Treeline Management, AI, Remote Sensing and Ecology in the Swiss Alps École Polytechnique Fédérale de Lausanne in Switzerland

EPFL (École Polytechnique Fédérale de Lausanne), Valais Wallis campus in Sion, Switzerland, is offering a full-time PhD position on forest treeline management in the Swiss Alps. The project sits at the intersection of artificial intelligence, deep learning, remote sensing, ecology, and forest dynamics, with a strong applied focus on climate and land-use change.

The successful PhD student will develop AI-based methods to map treeline evolution from high-resolution remote sensing data, then extend the work with ecological predictive models to forecast future treeline trends under climatic and planning scenarios. The research also includes analysing drivers of change in a land-use and climate-change context, and working closely with forest professionals through co-development workshops to define planning objectives and create management tools for practitioners.

Research themes and skills: AI-powered environmental monitoring, deep learning for spatial analysis, ecological and statistical forecasting, remote sensing, population ecology, Python programming, and stakeholder engagement/co-design.

Eligibility highlights: a master’s degree in environmental science and/or computer science; experience with remote sensing, ecological modeling, and population ecology; proficiency in Python and deep learning frameworks; fluent English; motivation to work in a dynamic interdisciplinary team.

Funding and contract: the post is a 100% PhD student position with competitive remuneration. The contract is a CDD, with 1 year for candidacy examination and up to 5 years total duration.

Application: shortlisted candidates will need to apply to the relevant EPFL Doctoral Program (EDCE) as part of the PhD admission process. The application package should include a motivation letter, CV, 3 referees, academic transcripts/diplomas, and ID/passport; an optional publication sample, master’s thesis, or semester project may also be included.

Start date: 9 September 2026.