We are seeking to appoint a full-time PhD Fellow to undertake research in a new project on Sustainable and efficient insect production for livestock feed through selective breeding (FLYgene). The PhD fellowship will focus on developing an Internet-of-Things (IoT) based platform for large scale identification and phenotyping of the Black Soldier Fly (BSF) in managed breeding sites within Kenya and Uganda. The PhD position will be primarily based at Makerere University (MAK), Uganda, with at least 1 year mandatory stay at Aarhus University (AU), Denmark. The proposed work hypothesizes that it is possible to develop efficient and affordable sensor-based methods, including computer-vision, to identify BSF at family level, and record phenotypes (focusing on traits such as growth rate, protein content and fitness) for selective breeding. Methods and tools combining mechanics, electronics, computer vision systems with illumination at different spectral wavelengths of light, and machine learning for automated recognition will be investigated. Initial experiments will be done at AU in Denmark and validated at MAK. Validated methods will be implemented to generate the phenotypic data at MAK and University of Nairobi (UoN).
For more details see the attached file below