Image Analysis & Machine Learning for Digital Plants & Crops
The Biomedical Imaging & Graphics lab at the University of Saskatchewan, Canada, led by Dr. Ian Stavness, has an immediate opening for fully funded MSc, PhD, Post-docs, full-time Research Associates and programmers in Computer Science / Engineering / Bioinformatics / Mathematics to work on big data analysis in plant biology and agriculture.
Successful candidates will contribute to the Plant Phenotyping and Imaging Research Center (P2IRC). I lead the Deep Learning for Phenomics flagship project focused on using image processing, computer vision, machine learning and computer graphics techniques to create high-resolution, statistical, and physics-based representations of plant and crop traits (phenotypes). These digital plant models will be used to associate genotypes with desirable traits and have the potential to revolutionize plant breeding processes worldwide.
We are searching for bright and enthusiastic individuals to join our team and make big data analysis in agriculture a reality. The ideal candidate will have strong computer programming skills and a keen interest in biological and agricultural research. Prior experience with image processing, digital signal processing, machine learning, pattern recognition, software engineering, robotics, and/or controls is also desirable.
You will join a dynamic, interdisciplinary team focused on developing next generation digital agriculture and supporting the world-wide community of plant breeders. You will also have the opportunity to interact with collaborators in imaging science at the Canadian Light Source synchrotron and in plant biology at the Global Institute for Food Security at the University of Saskatchewan.
Interested applicants should:
(1) Send an email indicating their interest and experience, a CV, and a PDF of their transcripts to ian.stavness@usask.ca (please use subject line "Deep Plant Phenomics position");
(2) Complete the short online form here