PhD in Computer Science: Sustainable AI for Plant Species Recognition in Tropical Forests

**Job Description**
This Ph.D. project seeks a motivated candidate to develop innovative artificial intelligence methods for plant species recognition from aerial imagery in tropical forests. The research will investigate the long-tailed open-ended semantic segmentation problem, advancing new approaches for uncertainty estimation and confidence-aware predictions. The successful candidate will join an international, interdisciplinary team and contribute to AI solutions with direct impact on biodiversity monitoring, conservation planning, and sustainable forest management.

**Skills & Abilities**
• Strong programming skills (Python preferred)
• Solid understanding of machine learning and deep learning, including computer vision techniques
• Ability to read, write, and communicate scientific texts clearly
• Strong analytical and problem-solving skills
• IELTS score of 6.5 overall, with no less than 6.0 in each component (if English is not first language)
• Experience with remote sensing or geospatial tools (e.g., QGIS) (Desirable)
• Previous experience publishing papers (e.g. from MSc/MRes/MEng projects) (Desirable)
• Interest or experience in ecology, biodiversity, or environmental monitoring (Desirable)

**Qualifications**
Required Degree(s) in:
• Computer Science
• Physics
• Mathematics
• Engineering
• Related field

**Experience**
Other:
• Applicants from other backgrounds with strong quantitative, programming, or analytical experience are also encouraged to apply.

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