Job Description

Description:

Research Associates:

Under the general direction of, and in collaboration with researchers and faculty members, positions at this level apply extensive knowledge in their field to perform high-level, complex research activities, and will normally hold a Master\xe2\x80\x99s degree. Individuals with training beyond a Master\xe2\x80\x99s degree who have limited experience may also be appointed into this classification level.

Position Overview:

TerraByte research group is seeking a highly motivated and experienced Research Associate to join our team and contribute to the development of new technologies in the field of image data generation and machine learning in agriculture. The successful candidate will be responsible for analyzing and processing digital agriculture data, designing, training, and testing deep learning neural network architectures and machine models for agricultural applications, and assisting with the design, assembly, and deployment of robotic camera systems and other embedded imaging platforms. The successful candidate will also learn about and participate in the activities presently ongoing in the project.

Duties and Responsibilities:

• Collaborate with a multidisciplinary team of researchers to enhance and optimize autonomous imaging systems for digital agriculture.
• Assist with the design, assembly, and deployment of robotic camera systems and other embedded imaging platforms.
• Implement technical upgrades to improve image quality and accuracy, ensuring reliable data collection and analysis.
• Conduct extensive analysis and pre-processing of digital agricultural image data, using Python and REST API, to derive valuable insights and support research objectives.
• Design, train, and test deep learning neural network architectures and machine models for plant identification, disease detection, and phenotyping tasks
• Integrate advanced plant segmentation algorithms into existing imaging systems, contributing to the removal of image background and improving the precision of data analysis.
• Collaborate closely with project stakeholders, including researchers, faculty, and industry partners, to ensure seamless coordination and successful project execution.
• Conduct academic-level research and literature searches.
• Participate in academic literature writing, to contribute to scholarly publications and research advancements in the field of digital agriculture.
• Contribute to reporting on research and activities, including communicating project outcomes, research findings, and activities with project stakeholders and members of the public.
• Contribute to overall activities and internal operations related to the research project.
• Perform other duties, as assigned.

Qualifications:

• A Bachelor\xe2\x80\x99s or Diploma degree in Data Science and Machine Learning, Computer Science, Agricultural Engineering, or a related field is required (Master\xe2\x80\x99s degree preferred).
• Formal training/education background in data science and machine learning.
• Prior experience in digital agriculture projects or related research is an asset.
• Experience in designing, training, and testing deep learning neural network architectures and machine models for agricultural applications.
• Strong programming skills, particularly in Python, with experience in REST API integration.
• Proficiency in image processing techniques and familiarity with advanced algorithms for plant segmentation and classification.
• Experience working with 3D drawing software and 3D printing is an asset.
• Experience with database management systems, including SQL and NoSQL databases.
• Strong knowledge of data visualization tools and libraries (e.g., Matplotlib, Tableau) for effective data presentation and analysis.
• Familiarity with deep learning frameworks such as TensorFlow, Keras, or PyTorch for image analysis and object detection.
• Experience with generative adversarial networks is a plus.
• Excellent problem-solving skills and attention to detail.
• Effective communication and teamwork abilities.
• Demonstrated ability to work independently and as part of a team in a dynamic research environment.
• Experience writing and publishing peer-reviewed articles.
• Experience writing technical reports.
• Experience writing for a general audience in a variety of formats and media, including print and online.
• Strong interest in interdisciplinary research and collaboration.
• Strong analytical skills and experience with data analysis tools and techniques.

Condition(s) of Employment:

• Must be legally entitled to work in Canada.

This position is eligible for extended health benefits, excluding pension.

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 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.

The University of Winnipeg is committed to ensuring employment opportunities are accessible for all applicants. If you require accommodation supports during the recruitment process, please contact human_resources@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\xe2\x80\x99s 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 human_resources@uwinnipeg.ca.

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 was 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.

University of Winnipeg