Deep Genomics is a startup company that aims to revolutionize drug development by leveraging expertise in artificial intelligence (AI) to decode RNA biology. Our proprietary platform, the AI Workbench, enables us to decode the enormous complexity of RNA biology to find novel targets, mechanisms, and molecules that are not accessible through traditional methods. We use this advanced technology to develop steric-blocking oligonucleotides (SBOs) that achieve expression increase for the treatment of genetic disease. Founded in 2015, our multidisciplinary team includes expertise in a diverse range of disciplines including those found in a traditional drug company, as well as machine learning, laboratory automation, and software engineering. Deep Genomics is based in Toronto, Ontario with an additional location in Cambridge, Massachusetts.

Where You Fit In

We are seeking a creative and talented Computational Biologist 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.

What you will do:

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.
Develop fast and accurate predictive workflows to support target validation and preclinical proof-of-concept for our oligonucleotide therapeutics.

What you bring:

A PhD in a quantitative discipline (e.g. Computational Biology, Computer Science, Applied Mathematics, Statistics, Biostatistics or Physics), or equivalent experience.
At least 2 years of experience with the development of novel algorithms/analysis pipelines for integrative analysis of genomics or other biological datasets.
Ability to design experiments, formulate hypotheses based on data, uncover causal mechanisms, and visualize data.
Working knowledge in machine learning modelling (e.g. neural networks, Bayesian methods, random forests, clustering).Proficient in Python or R.
Comfort working with limited supervision in a fast-paced and rapidly growing work environment.
You are a great communicator, highly organized and are willing to adapt to new situations quickly.

Nice to have:

Post-graduate experience (postdoc or industry).
Experience with RNA biology or antisense oligonucleotides.

What we offer:

A highly competitive salary and meaningful equity compensation (ESOPs)
A wide array of company-paid benefits
Exceptional opportunities for learning and growth working alongside a world-class team of researchers and software developers working at the intersection of the most exciting areas of science and technology.

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.

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