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Machine Learning Scientist

About Us

Novel therapeutics require novel methods.

ProteinQure is building a next-generation platform for the design of protein therapeutics. We partner with industry leaders in biologics drug discovery to generate novel therapeutics outside the scope of conventional procedures. Our expertise in molecular modelling, bioanalytical experiments, and machine learning enables us to search across vast spaces of therapeutics, and optimize lead candidates for desired properties using a scalable computing infrastructure.

To do that, we’ve built a team defined by courage and determination. It doesn't matter whether you are inventing novel machine learning techniques, reimagining life science partnerships or designing cutting edge experiments; working with us involves having the courage to reinvent the status quo and the determination to see it through.

About You

We're looking for a Machine Learning Scientist to join our team in Toronto, Canada. You’re a scientist or engineer driven to confront challenging unsolved problems by leveraging the world’s most cutting-edge technologies. You excel in fast-paced environments. You are interested in exploring how to integrate human expertise and computational tools to design new chemical entities.


Responsibilities

  • Perform research and development of new methods for learning from protein sequence and structure datasets
    • Unsupervised learning of protein/peptide sequence representation to assist in downstream machine learning engineering within the platform
    • Development of supervised learning algorithms for protein structure prediction, protein-protein interaction prediction, and iterative optimization of therapeutics.
    • Construction of novel protein sequence-structure-function datasets (public, private data sources, from experimental or computational measurements)
  • Work side-by-side with chemists, biologists, computer scientists, and software developers to develop drug candidates using our protein design platform
    • Apply machine learning models to assist science team in protein design
    • Assist software engineering team in deployment of ML tools at scale

Nice to haves:

  • Peer-reviewed publications on applications of machine learning in biology, or new methods in natural language processing or computer vision
  • Academic background in statistics, linear algebra, numerical computing
  • Basic knowledge of biology, familiarity with biological data (sequence, structure)
  • Experience working with multiple developers with distributed version control (Git)

Requirements:

  • PhD in Computer Science, Statistics or similar field
  • Experience with Python and one or more deep learning libraries (Tensorflow, Keras, PyTorch)
  • Comfort explaining technical concepts to a diverse audience

Compensation:

  • A competitive mix of equity and salary
  • Unlimited vacation
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