M.Sc. - Evaluation and modelling of gilt fertility traits

Position: M.Sc. - Evaluation and modelling of gilt fertility traits

OAC Academic Unit: Department of Animal Biosciences

Start date: September 2022 or January 2023

Advisor Name: Dr. Dan Tulpan (dtulpan@uoguelph.ca)

Duration: 2 years

Stipend: $22,000/year

Project Description

This project is a collaboration with the Canadian Center for Swine improvement, and it will focus on exploring evaluation and modelling approaches for pig fertility traits using a combination of physiological, physical and environmental data collected on farms. The student will be trained to use sensors to collect data on farm and effectively apply various modeling approaches including but not limited to machine/deep learning to test hypotheses and identify relevant features for predictive purposes.

In addition, the MSc student will work in a team of undergrad/grad students, postdocs and professors to accomplish the above tasks. The project also financially supports travel costs and attendance to a workshop and a conference.


Required skills: The M.Sc. candidate should have a strong background in animal biosciences with additional knowledge of computational and modeling techniques. They must have an honours BSc degree in biology, animal science or a related field with a minimum B average (75%). They must have proven experience performing a literature review, fieldwork, basic modelling/programming knowledge and statistical analysis (e.g. R). The candidate should be self-motivated to learn, an independent worker, able to problem solve and have a critical thinking mindset. They should be able to work well within a group and have strong written and oral communication skills. The University of Guelph believes in improving equity, diversity and inclusion in its study programs and workplaces; thus all applicants are welcome who meet the above required skills.

Preferred skills: A successful candidate would have an A average, exposure to using a Linux environment and have basic programming skills in Python and R.

Application Instructions

Qualified candidates should send their CV, transcripts, and cover letter (one-page) to Dr. Dan Tulpan (dtulpan@uoguelph.ca) with the subject “MSc thesis application - 499200”.

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