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PhD in Data-driven Plant Phenotyping for Sustainable Agriculture
2 months ago
Aarhus Universitet is seeking a highly motivated PhD researcher to contribute to the development of novel crop plants for sustainable agriculture.
Research Area and Project DescriptionIn the pursuit of urgent sustainable intensification, modern agriculture faces the challenge of transitioning to climate-friendly, diversified, and resource-efficient systems for food, feed, and energy production. Perennial grain crops are emerging as a promising solution, requiring fewer inputs and possessing deep root systems, making them more resilient against adverse climate conditions as well as sustainable with greater soil carbon sequestration potential.
Despite the rigorous efforts, however, the adoption of these wild plants has been incremental due to the difficulties in developing owing to complex gene and laborious genomic selection processes. Therefore, faster and more efficient identification of perennial traits and candidates for further development is necessary, for example, for a decent grain yield and solid survival over the season.
Project Objectives- Developing UAV image analysis-software by exploiting images from high-spectral and LiDAR sensors to identify superior grain/spike structure and early traits of perennial wild plants with data fusion/deep learning algorithms.
- Developing MicroCT image analysis-software/algorithm for root phenotyping to identify more rigorous, resource-use efficient and resilient root traits following repeated canopy removal of perennial wild plants.
- Validating phenomic selection of perennial wild types based on the generated digital datasets using the developed pipelines against the genomic data in collaboration with breeders.
To achieve these goals, the PhD candidate will collaborate with researchers from the Department of Electrical and Computer Engineering (ECE) at AU. Furthermore, a close cooperation with The Land Institute (TLI) in the United States is foreseen for validating the phenomic selection carried at AU.
The successful candidate will have the opportunity to work closely with interdisciplinary teams, utilize cutting-edge technologies, and generate novel datasets, algorithms, and phenotyping software that will be widely used by the plant community in a long run.
Qualifications and CompetencesYou are:
- A data scientist/computer programmer with background knowledge in biology/genetics.
- Alternatively, you are a biologist/plant scientist with in-depth knowledge and experience in data science and computer programming.
Required qualifications:
- Master's degree in data science, computer programming, computer vision, computer engineering, computational biology, agricultural engineering, biology, or equivalent degree.
- Excellent and documented experience in software engineering and coding skills in deep learning.
- Experience with analyzing biological images.
- Experience or commitment to generate datasets in crop field conditions and medical imaging set up.
- Proven ability to work independently and take initiative in research projects.
Add-ons:
- Understanding in plant science/genetics/breeding.
- Strong team-oriented attitude.
Aarhus Universitet is an equal opportunities employer and welcomes applications from all qualified candidates. The university is committed to creating an inclusive and diverse work environment.
