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- To assess unique attributes associated with individual kernels during distinct sprouting phases in Canadian Western Red Spring (CWRS) wheat. These attributes encompass germ dimensions and conditions, color pigments, variability in grayscale, and alterations in pixel intensity.
- To quantify the alpha -amylase activity in wheat affected by sprouting using NIR spectrometry.
- To construct an efficient classifier, such as algorithms or neural networks, that establishes a correlation between alpha-amylase activity and imaging attributes for various wheat varieties under examination.
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- Designing and fabricating a machine vision system
- Programming or coding for imaging analysis and neural network/deep learning.
- Publishing research results in reputable peer-reviewed scientific journals.
- Following safe laboratory procedures.
- Demonstrated ability to use software for imaging analysis and neural network/deep learning.
- Demonstrated ability to use NIR spectrometry.
- Demonstrated ability to create and foster relationships with people of diverse backgrounds and education levels.
- Demonstrated ability to present research results.
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Post-Doctoral - Chemical & Biological Engineering (Machine Vision) - Saskatoon, Canada - University of Saskatchewan
Description
Post-Doctoral - Chemical & Biological Engineering (Machine Vision)
Dr. Oon-Doo Baik and collaborators are currently seeking a postdoctoral fellow to join an exciting research project. The focus of this project is to develop a machine vision system to assess sprout damage of wheat. The project requires fabrication of the dual camera machine vision system based on artificial neural network/deep learning and quantification of alpha-amylase activity in sprout affected wheat.
The project is funded through the from ADF Program. This is therefore a 3-year position, provided satisfactory performance during the probation period.
Nature of Work:
The primary responsibilities of the Postdoctoral Fellow will be to conduct research associated with the ADF program. This project involves investigating the development of an efficient classifier to correlate alpha-amylase activity with imaging attributes detected by a dual camera machine vision system. The post-doc will build the machine vision system for this project. Other duties include, but are not limited to, and presenting data, and writing scientific manuscripts. Collaboration with colleagues, keeping laboratory spaces clean and organized, assistance with laboratory procedures, data analysis, assistance with meeting organization and presentations to research project meetings.
Typical Duties or Accountabilities:
Qualifications
Education:
A PhD degree in Computer Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, Agricultural Engineering, or a related discipline, preferably with experience in machine vision fabrication, image processing, and AI algorithms or neural networks. Candidates in the final stages of their PhD studies will also be considered, as long as there is a clear timeline for completion (within two months for defense).
Experience:
The successful candidate should have experience in:
Skills:
