Uncubed
   

Scientist - Computational Biology

Deep Genomics, Toronto/Boston/San Francisco Bay Area/Remote North America Only

Creating A New Universe Of Genetic Medicines

Duration: Full-Time


About Us 

We are a Toronto-based startup company that is building an AI-powered discovery and development platform to significantly expand the universe of medicines available for genetically-defined diseases. Founded in 2015, we bring together a multidisciplinary team of world-leading experts in machine learning, genomics, chemistry, and biology. Together we are on a mission to rapidly discover and develop oligonucleotide drugs for the treatment of patients with severe disorders of the liver, central nervous system, and eye.

About the role

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 do 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.
  • You are a great communicator, highly organized and are willing to adapt to new situations quickly.
  • Comfort working with limited supervision in a fast-paced and rapidly growing work environment.

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 the world’s best team.
  • An opportunity to work alongside a bright, collegial, highly motivated team working at the intersection of the most exciting areas of science and technology.
Deep Genomics encourages applications from all backgrounds who seek the opportunity to build the world's leading AI-driven genetic medicine company. 

If you have a disability or special need, accommodation is available on request for candidates taking part in all aspects of the selection process.

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.

Deep Genomics

Want to learn more about Deep Genomics? Visit Deep Genomics's website.