As Austria's largest research and technology organisation for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and difitalisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria's leading research institution at the highest international level and to make a positive contribution to the economy and society.
 
Our Center for Vision, Automation & Control located in Vienna invites applications for a master’s thesis position. At the Center for Vision, Automation & Control our research unit “Assistive & Autonomous Systems” closely works with industrial partners in order to develop safe and reliable technology components for assistance systems, that can be used in various areas of applications, for e.g.: Railway / Public Transport, Construction Industry, Logistics & Transportation, Agriculture & Forestry as well as in Aviation.
 
Our research focuses on developing advanced deep learning frameworks to predict plant phenotypes, such as “yield potential” and “disease severity”, in winter wheat using UAV-acquired multispectral data. Our aim is to build a scalable framework that leverages time-series multispectral images for efficient and accurate phenotype prediction

• Throughout this master’s thesis, you will closely work with our researchers and engineers, who focus on the development and deployment of assistive and autonomous systems, particularly unmanned aircrafts and land-based mobile machines – Hereby you will communicate and engage with a multi-disciplinary team to solve diverse multi-facetted challenges.
• Under the guidance of our experts, you will contribute to a rapidly growing field in aerial robotics.
• You will investigate the state-of-the-art and apply it in real-world scenarios and – as a final step – will design a proof-of-concept demonstration.
• You design, develop, and optimise deep learning models for processing time-agnostic multispectral image data.

• You adapt and benchmark our model to improve the prediction of winter wheat phenotypes.
• You preprocess and manage large-scale UAV-acquired multispectral datasets.
• You collaborate with an interdisciplinary team of researchers in a supportive and dynamic environment.
• You participate in interpreting model predictions in real-world agricultural applications.
• You conduct in-depth analysis and reporting of results, focusing on model interpretability and performance.