Master Thesis on Hyperspectral Photosynthetic Phenotyping of Winter Wheat

09.03.2026, Abschlussarbeiten, Bachelor- und Masterarbeiten

What You Will Gain

• Technical skills: End-to-end hyperspectral data processing, from acquisition to analysis.
• Modeling experience: Training in statistics, machine learning/deep learning, with guidance and support.
• Physiological insight: Understanding how spectral signals and traits evolve across winter wheat growth stages.

• Field sampling: 4–5 data collection campaigns from April to July 2026, each lasting 1–3 days.
• Phenotyping: Simultaneous acquisition of hyperspectral data and photosynthesis-related traits.
• Thesis: Explore spectral–phenotypic relationships and complete the thesis.

Who We Are Looking For

We are looking for a motivated student with an interest in plant phenotyping or smart agriculture, who has basic data processing skills and is comfortable with field sampling work.

If you are interested in this thesis opportunity, please send a brief statement of motivation or your CV.

Kontakt: ying.yuan@tum.de