Graduate Research Intern (Computational Biology)
Deepgenomics in Toronto, Ontario
About Us
Founded in 2015, Deep Genomics is a drug development company that aims to revolutionize medicine by leveraging expertise in artificial intelligence (AI) and genome biology. We have built the world’s first, and by far the most advanced, AI platform that is able to untangle the enormous complexity of RNA biology and find the best targets, mechanisms, and molecules. We take immense pride in our team of people whose backgrounds span a diverse range of disciplines including those found in a traditional biotechnology company, as well as machine learning, laboratory automation, and software engineering.
Where You Fit In
We are seeking exceptional graduate students for an 8 to 12-month internship with an interest in using machine learning, large datasets and automation to revolutionize drug development. You will work regularly with and learn from our multilingual team of machine learning scientists, software engineers, computational biologists, molecular geneticists, and wet-lab scientists to help design oligonucleotide therapies.
Deep Genomics thanks all applicants, however only those selected for an interview will be contacted.
Deep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.
- 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 (e.g. MSc, PhD) 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.
- Inspiring, creative and fast-moving startup located right next to the University of Toronto and within the MaRS Discovery District – an expanding hub of research in AI and genomics
- Exceptional opportunity to work alongside a bright, collegial, highly motivated team working at the intersection of the most exciting areas of science and technology
- Competitive compensation package