Fully Funded PhD Scholarship: Forest Treeline Management – EPFL Switzerland
About EPFL (Swiss Federal Institute of Technology Lausanne)
Applications are open for a PhD position in Forest Treeline Management at EPFL Valais Wallis in Sion, Switzerland. EPFL is consistently ranked among the world’s leading universities for science, engineering, technology, and innovation. The institution hosts more than 18,500 students and researchers from over 120 nationalities, offering a highly international academic environment with world-class research infrastructure and strong industry and governmental collaborations.
Scholarship Overview
Project Description
Forest treelines are among the most sensitive ecological boundaries affected by climate change and land-use transformations. Understanding how treelines shift over time is critical for biodiversity conservation, forest management, climate adaptation planning, ecosystem resilience, and sustainable land-use policies. This PhD project aims to develop innovative technological solutions that help scientists and policymakers better understand and manage forest treeline dynamics across the Swiss Alps. The successful candidate will combine artificial intelligence, remote sensing technologies, ecological forecasting, and stakeholder engagement to create practical management tools for future forest planning.
Why This Scholarship Stands Out
This PhD is unique because it combines artificial intelligence, remote sensing, and ecological modeling to address one of the most visible impacts of climate change: shifting forest treelines in the Alps. You will develop deep learning models for treeline mapping using high-resolution remote sensing data, investigate historical treeline dynamics, and forecast future changes under climate and land-use scenarios. The project includes stakeholder engagement with forestry professionals and environmental managers – translating research into practical decision-support tools. EPFL is one of the world’s leading technical universities, and the position offers full-time employment with a competitive Swiss doctoral salary. For a student interested in AI, environmental science, and climate adaptation, this is an opportunity to do research with direct policy relevance.
Key Responsibilities
- Develop deep learning methodologies for treeline mapping
- Process and analyze high-resolution remote sensing data
- Monitor forest dynamics across space and time
- Build AI-based environmental assessment tools
- Develop predictive ecological models
- Analyze climate and land-use impacts
- Forecast future treeline shifts
- Organize co-creation workshops with forestry professionals and environmental stakeholders
- Design innovative digital tools for decision-support
- Publish research articles in peer-reviewed journals
- Present findings at international conferences
Candidate Profile and Eligibility
| Requirement | Details |
|---|---|
| Education | Master’s degree in Environmental Science, Computer Science, Ecology, Geospatial Science, Remote Sensing, or related discipline |
| Technical Skills | Python programming, deep learning frameworks, AI applications, remote sensing analysis, geospatial data processing |
| Scientific Background | Ecological modeling, population ecology, environmental analysis, climate change research |
| Communication | Strong English proficiency, scientific writing abilities, team collaboration skills, stakeholder engagement capabilities |
| Personal Qualities | Motivated, curious, innovative, enthusiastic about interdisciplinary research |
What They Offer
| Benefit | Details |
|---|---|
| Employment | Full-time (100%) with competitive Swiss doctoral salary |
| Contract | Fixed-term (CDD) with one-year candidacy examination phase and extension up to five additional years |
| Start Date | September 1, 2026 |
| Location | Sion, Switzerland (EPFL Valais Wallis) |
| Research Environment | World-class infrastructure, international academic environment, strong industry and governmental collaborations |
| Training | AI, deep learning, environmental data science, climate adaptation research, ecological forecasting |
My Application Tips
- Highlight your Python and deep learning experience – AI methodologies are core to this project
- Emphasize remote sensing and geospatial data processing skills – High-resolution data analysis is key
- Show ecological modeling or climate change research background – Understanding of treeline dynamics
- Demonstrate stakeholder engagement or science communication experience – Workshops and decision-support tools
- Prepare for separate EPFL Doctoral Program admission – Shortlisted applicants must apply to the EDCE Doctoral Program
Who Should Apply
This PhD is perfect for a student with a background in environmental science, computer science, remote sensing, or ecology who wants to apply AI to climate adaptation challenges. If you are interested in how machine learning can help monitor and predict forest treeline shifts in the Alps, and want to work with stakeholders to create practical management tools, this project offers training across deep learning, remote sensing, ecological modeling, and science communication.
How to Apply
Apply through the EPFL application portal.
Required documents:
- Letter of interest (maximum two pages) explaining motivation and qualifications
- Updated Curriculum Vitae (CV)
- Contact details for three referees
- Academic transcripts and degree certificates
- Master’s enrollment certificate (if degree completion pending)
- Passport or official identification document
Optional documents:
- Published research papers
- Master’s thesis
- Research projects
- Academic writing samples
Important: Shortlisted applicants must also apply separately to an EPFL Doctoral Program (EDCE Doctoral Program) for admission. contacted. The selection process may conclude early if appropriate applicants are secured.
