Research Assistant, TerraByte (Digital Agriculture Project)

Job title: Research Assistant, TerraByte (Digital Agriculture Project)

Job description: Description:

Research Assistants are normally students, in a University of Winnipeg undergraduate program, employed to assist with tasks related to research. Work is performed within defined guidelines and under supervision of a more senior researcher or faculty member.

Position Overview:

The successful candidate will join a large collaborative research project involving multiple academic institutions and industry partners. The focus of this project is to compare existing machine learning models with polynomial neural networks for localization of plants in digital images for agricultural applications. The research assistant will work primarily on reviewing literature, machine learning model development, training, and testing. They will also learn about and participate in the activities presently ongoing in the project.

Duties:

• Work in a collaborative team environment, under the general direction of Drs. Christopher Henry and Christopher Bidinosti.
• Conduct high-level academic literature reviews and associated writing tasks, especially as it relates to object localization within digital images and polynomial neural networks.
• Analyze and pre-process digital agricultural image data.
• Design, train, and test deep learning neural network models.
• Draft technical report on final solution.
• Contribute to academic and popular publications related to project research.
• Other duties, as assigned.

Qualifications:

• Master’s degree.
• Formal training/education in computer science, mathematics, statistics, and machine learning.
• Excellent oral and written communication skills.
• Excellent organizational skills with the ability to manage time effectively and efficiently to meet deadlines.
• Strong interpersonal skills with the ability to work as part of a team.
• Machine learning experience related to digital agriculture applications.
• Experience working with digital agricultural data.
• Knowledge of and experience with Python, PyTorch, and TensorFlow.

Condition(s) of Employment:

• Must be legally entitled to work in Canada.

The period of work will be from May 2, 2022 – August 31, 2022 and the estimated total hours of work will be 660 hours.

Note: This position is represented by the Public Service Alliance of Canada – Research Capacity Unit.

Note: The work described in this posting will be conducted in-person.

The University of Winnipeg has a Mandatory COVID-19 Vaccination Policy that requires all those coming to designated indoor campus spaces to provide proof they are fully vaccinated. The Policy will be suspended effective May 2, 2022. However, prospective employees should know that the Policy may be reinstated in the future based on changing public health circumstances.

The University of Winnipeg is committed to equity, diversity and inclusion and recognizes that a diverse staff and faculty benefits and enriches the work, learning and research environments, and is essential to academic and institutional excellence. We welcome applications from all qualified individuals and encourage women, racialized persons, Indigenous persons, persons with disabilities, and 2SLGBTQ+ persons to confidentially self-identify at time of application.

If you require accommodation supports during the recruitment process, please contact Shelby Phillips, HR Assistant at sh.phillips@uwinnipeg.ca.

The personal information of applicants is collected under the authority of the University of Winnipeg Act and 36(1)(b) of the Freedom of Information and Protection of Privacy Act. All personal information collected via the recruitment process is used to assess the applicant’s suitability, eligibility, and qualifications for employment, and to otherwise support recruitment activities. This information will be provided to participating members of the recruitment process. Questions regarding the collection of your personal information may be directed to the Director, HR Services, 515 Portage Avenue, Winnipeg, MB, R3B 2E9 or 204.786.9066.

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