Graduate Research Intern (Computational Biology)
Deep Genomics, Toronto, Ontario
Creating A New Universe Of Genetic Medicines
- Aid the design of wet-lab experiments to investigate novel and existing RNA regulatory mechanisms.
- Analyze high-throughput drug and sequencing data (e.g. RNA-seq, CLIP-seq, MPRAs, Perturb-seq) to help build machine learning models and design novel antisense oligonucleotides.
- Apply machine learning models to design novel antisense oligonucleotides.
- Interrogate how antisense oligonucleotides interact with regulatory mechanisms to achieve its effect.
- Are currently enrolled in a graduate program in Computer Science, Electrical or Computer Engineering, Mathematics, or a related discipline.
- Experience with the development of algorithms/analysis pipelines for integrative analysis of biological datasets.
- Working knowledge in machine learning modelling (e.g. neural networks, Bayesian methods, random forests, clustering), probability and statistics.
- Proficient in Python or R.
- You are a great communicator, highly organized and are willing to adapt to new situations quickly.
- Experience working with wet labs to develop genomics assays.
What we offer
- A highly competitive salary.
- An opportunity to work alongside a bright, collegial, highly motivated team working at the intersection of the most exciting areas of science and technology.
About Deep Genomics
Deep Genomics is using artificial intelligence to build a new universe of life-saving genetic therapies. The future of medicine will rely on artificial intelligence, because biology is too complex for humans to understand. At Deep Genomics, our geneticists, molecular biologists and chemists develop new ways of detecting and treating disease using our biologically accurate artificial intelligence technology.
Want to learn more about Deep Genomics? Visit Deep Genomics's website.
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