Previous M.Sc./Ph.D. Opportunities
Please note that these positions have been filled and are no longer available. Refer to Current M.Sc./Ph.D. Opportunities for available positions.
Graduate Student Opportunity in ECOLOGY/BIOINFORMATICS
Dr. Karl Cottenie (Integrative Biology)
ABOUT THE PROJECT
A MSc/PhD graduate student position is available in the laboratory of Dr. Cottenie in the Department of Integrative Biology in the College of Biological Science (www.cottenielab.org). The main research theme in my lab (www.cottenielab.org) centers around metacommunity dynamics, and we study this in a wide variety of systems, from fish to small mammals to macroinvertebrates to transposable elements within the genome. I am currently expanding my research focus to microbiome studies, and the first system that I will study is the microbiome of Canada Jays in Algonquin Park. Some of the questions we are interested in are determining the effect of very local dispersal (vertical transmission from parents to offspring) and regional dispersal (dispersal of parents and offspring in the landscape) on the oral and gut microbiome of Canada Jay individuals.
REQUIREMENTS
I am looking for an enthusiastic graduate student who wants a research project that combines ecological field work with bioinformatics to study relevant questions in ecology through advanced statistical analyses in R. This position is open to Canadian citizens or permanent residents. Other strong candidates are also welcome to apply.
Evaluating changes in the tonsil microbiome in Streptococcus suis disease in pigs
Dr. Nicole Ricker (Pathobiology)
There are two research opportunity focus possibilities:
1. Microbiology/AMR/Pathogenomics:
Through this work, students will develop important bioinformatics skills and techniques for analyzing genomic and metagenomic data from a diversity of next-generation sequencing technologies and relate these to the disease status of the animals and other research questions. Projects could include shotgun sequencing of microbiome samples and functional analysis of bacterial communities; mixed Enterobacteriaceae enrichment plasmid extractions and long-read sequencing assembly; bio-marker discovery and development of tools for monitoring AMR and pathogens in the food chain and the environment.
2. Predictive Modeling and Big Data Initiatives:
Students will utilize machine learning techniques to evaluate shotgun sequencing data for their ability to track bacterial pathogens and predict disease development. Projects include comparative genomics of bacterial isolates for specific traits relating to disease development, as well as shotgun metagenomics of microbiome samples to reveal relevant functional categories that correlate with improved health outcomes. Students will learn the importance of annotation and standardization in publicly available databases, and use data mining techniques to identify taxonomic or functional bio-markers that can be integrated into decision support tools for livestock production.
M.Sc. Position in Computational Biology (Dairy)
Dr. Dan Tulpan (Animal Biosciences)
The project will focus on computational/automatic detection and monitoring of antibiotic usage in dairy cattle. We will collaborate with OVC and Lactanet researchers.
Candidates must be interested in learning new computational analytical tools, advanced modeling techniques and learn how to write code to automate tasks.
Ph.D. student sought to study soil biodiversity using bioinformatics tools & state-of-the-art environmental DNA technology
Dr. Sarah (Sally) Adamowicz & Dr. Rob Hanner (Integrative Biology)
POSITION DESCRIPTION: We are seeking a strong and independent graduate student to study soil biodiversity and its response to varied restoration practices using state-of-the-art environmental DNA technology and bioinformatic tools for data analyses. The candidate will be involved in developing novel molecular approaches to study soil biodiversity across multiple taxonomic levels including both prokaryotes and eukaryotes. The research will include opportunities to study species interactions (e.g. plant root microbiome) and the efficacy of varied soil amendments that could help accelerate ecological succession across soil disturbance gradients. The research will take place in the boreal forest of Northern Ontario and relates to mining operations taking place there. The selected candidate will gain experience in bioinformatics, molecular biology, spatial ecology, environmental chemistry, and environmental restoration. The candidate will be part of a collaborative research team that seeks to study biodiversity moderation at the landscape scale. The applicants should hold a M.Sc. degree in one of the following fields: Bioinformatics, Biology, Biotechnology, Molecular Biology, Soil Science, or in any other program that is relevant to the proposed research activities. The principal laboratory is located at the University of Guelph’s Biodiversity Institute in Guelph (ON, Canada). The candidate will also interact with colleagues from Kirkland Lake Gold Corp, the University of Saskatchewan, and multiple faculty members from Guelph. The project will begin in either May 2022 or September 2022.
PROGRAM CHOICE: This project includes both analytical and biological research components. Depending upon the applicants' background and primary research interests, the selected student could enroll through either the PhD program in Integrative Biology or the PhD program in Bioinformatics, University of Guelph.
Gaze Tracking: MSc student(s) projects related to gaze planning and tracking
Dr. Maz Fallah (Human Health & Nutritional Sciences)
POSITION DESCRIPTION: They say the eyes are a window to our souls. We continue to show how the eyes intrinsically reflect other brain functions. To this end, we are seeking a graduate student to study how eye movements reflect underlying cognitive and perceptual processing, in health and disease. The candidate will investigate how gaze reflects feature- and object-based visual processing, decision-making, target selection, and cognitive strategies. The research involves designing experiments using infrared eye trackers, analyzing gaze metrics, and using the results to advance our understanding of how we process the world around us to be able to act upon it. There is the potential to advancing our computational models and develop neural network models. The successful candidate will have a relevant background (e.g. neuroscience, human kinetics, psychology, cognitive science, biomedical science, informatics, etc) and preferably some programming skills (e.g. Matlab).
MSc Position to Study Erythrocyte Fatty Acid Signatures Associated with Dairy Intakes and Cardiometabolic Disease Risk Factors in a Canadian Population
Dr. David M Mutch (Human Health and Nutritional Sciences)
PROJECT DESCRIPTION: Dairy foods and beverages provide various nutrients that are important for health and development, including vitamins, minerals, protein, carbohydrates, and fatty acids. Despite this, many Canadians are eating less dairy due to contradictory messaging about its effect on health. The relationship between dairy and health is complex, and may depend on the amount of dairy consumed, the type of dairy consumed, and the overall fat content of the dairy consumed. These differences may be due to the varying fatty acid compositions of different dairy products that can then modify blood fatty acid profiles in distinct ways. This is particularly important because blood fatty acid profiles are now considered markers of disease risk. The overall goal of this research project is to apply supervised and unsupervised clustering methods to investigate the relationships between dairy intakes, blood fatty acids, and risk factors for common diseases in a representative Canadian population using data collected in the Canadian Health Measures Survey (CHMS) study by Stats Canada.
The successful candidate will use supervised and unsupervised clustering techniques, as well as multiple linear regression, to explore the relationship between blood fatty acid profiles in different dairy intake groups and their associations with quantitative cardiometabolic risk markers in ~4,000 Canadians. The data used was collected as part of the Canadian Health Measures Survey (CHMS) study by Statistics Canada and will be accessed through a secure Stats Canada facility at the University of Guelph main campus.