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Graduate Research Intern (Computational Biology)

Deep Genomics, Toronto, Ontario

Creating A New Universe Of Genetic Medicines

Duration: Internship


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. 

The thesis here at Deep Genomics is that everyone, at some point in their life, will face a genetic condition, whether Mendelian or complex, and we aim to be there for them with a genetically precise therapy. 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. 

We are rapidly growing and are looking for key people to help us achieve our goals. We are currently looking for a Computational Biologist based at Boston/Toronto/Remote North America.

Opportunity
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.

Your responsibilities

  • 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. 

Requirements

  • 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.

Optional Requirements

  • 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.
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.

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.