Postdoc (Machine Vision)

Post-Doctoral - Chemical & Biological Engineering (Machine Vision) 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 2024-2027 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:

• Implementation and deployment of dual camera machine vision system consisting of a smart camera integrated with custom-designed state-of-the-art imaging software, lighting, display capabilities, and a sample presenter.
• 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.
• Other duties as assigned.

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:

• 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.

Skills:

• 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.

To Apply: Applications will be accepted by email and must include a cover letter, a statement addressing qualifications, and resume, and be submitted as a single PDF document. Review of applications will start from April 25, and continue until a suitable candidate is found.

Inquiries regarding this position can be directed to Dr. Oon-Doo Baik (oon-doo.baik@usask.ca).

Department: Chemical & Biological Engineering
Status: Term
Employment Group: Post-Doctoral Fellows - PSAC
Full Time Equivalent (FTE): 1.0
Salary Information: The starting salary will be commensurate with education and experience.
Posted Date: 4/9/2024
Closing Date: Until filled
Number of Openings: 1
Work Location: On Campus

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 2024-2027 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:

• Implementation and deployment of dual camera machine vision system consisting of a smart camera integrated with custom-designed state-of-the-art imaging software, lighting, display capabilities, and a sample presenter.
• 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.
• Other duties as assigned.

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:

• 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.

Skills:

• 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.

To Apply: Applications will be accepted by email and must include a cover letter, a statement addressing qualifications, and resume, and be submitted as a single PDF document. Review of applications will start from April 25, and continue until a suitable candidate is found.

Inquiries regarding this position can be directed to Dr. Oon-Doo Baik (oon-doo.baik@usask.ca).

Department: Chemical & Biological Engineering
Status: Term
Employment Group: Post-Doctoral Fellows - PSAC
Full Time Equivalent (FTE): 1.0
Salary Information: The starting salary will be commensurate with education and experience.
Posted Date: 4/9/2024
Closing Date: Until filled
Number of Openings: 1
Work Location: On Campus

The University is committed to employment equity, diversity, and inclusion, and are proud to support career opportunities for Indigenous peoples to reflect the community we serve. We are dedicated to recruiting individuals who will enrich our work and learning environments. All qualified candidates are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadian citizens and permanent residents will be given priority. We are committed to providing accommodations to those with a disability or medical necessity. If you require an accommodation to participate in the recruitment process, please notify us and we will work together on the accommodation request. We continue to grow our partnerships with Indigenous communities across the province, nationally, and internationally and value the unique perspective that Indigenous employees provide to strengthen these relationships. Verification of Indigenous Membership/Citizenship at the University of Saskatchewan is led and determined by the deybwewin | taapwaywin | tapwewin: Indigenous Truth policy and Standing Committee in accordance with the processes developed to enact the policy. Successful candidates that assert Indigenous membership/citizenship will be asked to complete the verification process of Indigenous membership/citizenship with documentation. The University of Saskatchewan’s main campus is situated on Treaty 6 Territory and the Homeland of the Métis. We pay our respects to the First Nations and Métis ancestors of this place and reaffirm our relationship with one another. Together, we are uplifting Indigenization to a place of prominence at the University of Saskatchewan. #J-18808-Ljbffr

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