Tom Ouellette
PhD Candidate, Computational Biology
Old Toronto, Ontario, Canada
Summary
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Senior🎓
Top SchoolTom Ouellette is a PhD candidate in Computational Biology at the University of Toronto with eight years of research experience applying machine learning and single-molecule technologies to study cancer evolution and ecology in the Awadalla Lab. He combines a strong experimental background in pharmacology and genomics from UBC with computational expertise developed through projects across BC Children’s Hospital, Cannevert Therapeutics, and genome evolution work at UBC. Tom’s work focuses on extracting evolutionary insights from high-resolution molecular data, translating complex biological signals into models that reveal tumor dynamics. He is comfortable bridging wet-lab and computational teams, and his profile suggests a knack for hands-on innovation in lab technologies as well as reproducible analysis pipelines.
8 years of coding experience
Bachelor of Science (BSc), Honours Pharmacology, Minor in Biology, Distinction/Co-op, Bachelor of Science (BSc), Honours Pharmacology, Minor in Biology, Distinction/Co-op at The University of British ColumbiaDoctor of Philosophy (PhD), Molecular Genetics (Computational Biology Track), Doctor of Philosophy (PhD), Molecular Genetics (Computational Biology Track) at University of Toronto
Github Skills (76)
annotations10
singularity9
reproducible-science9
labeling9
nextflow9
pipeline9
computer-vision9
slurm9
datasets9
standardized9
label-studio9
label9
reproducible-research9
text-annotation9
bioinformatics9
Programming languages (8)
Github contributions (5)
tomouellette/TumE
Nov 2021 - Jun 2022
Inferring cancer evolution using synthetic supervised learning
Contributions:32 commits, 2 PRs, 17 pushes in 7 months
pytorchautoencodersupervised-learningevolutionsupervised
tomouellette/ImHapE
Sep 2020 - May 2023
Image-based haplotype-guided evolutionary inference (IHapE)
Contributions:2 PRs, 39 pushes, 2 branches in 2 years 8 months
evolutionaryinferenceguided
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