Machine Learning Scientist (Biology or Chemistry Experience)

at  PROTEINQURE INC

At ProteinQure, we are building a computational platform for design of protein therapeutics. Our mission is to help to create a world where drugs are engineered, not discovered. We work on treatments for cancer, diabetes, asthma, and cardiovascular diseases, among others, and partner with industry leaders in drug discovery to generate novel therapeutics outside of the conventional chemical space.
Our technology combines computational biophysical models with statistical and machine learning approaches to enable us to search across vast spaces of protein therapeutics. We build and deploy these computational modules using a scalable cloud computing infrastructure and complement their predictions with results from wet lab experiments. We utilize advanced computing architectures based on high-performance GPUs, TPUs and investigate novel methodologies in biophysical modelling and quantum computing.
We’re looking for a Machine Learning Scientist to join our team in Toronto (Canada). You should think about joining us if you enjoy using state-of-the-art machine learning algorithms in high impact applications.
We are building out our computational RD team. We are adding members with experience in applying machine learning to biology (and chemistry) systems complement other team members who are leaders in the field of biophysical computational methods. It is a interdisciplinary team with many opportunities for growth and impact.

REQUIREMENTS:

• PhD in relevant field OR or multiple years of working experience
• Knowledge of biology, familiarity with biological data (sequence, structure)

• 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 protein property prediction
• Work with data sets that are diverse in type and size (sparse/big data sets, 3D models, amino acid sequences, structural features)
• Work side-by-side with chemists, biologists, and software engineers to develop drug candidates
• Assist software engineering team in deployment of ML tools at scale
• Help create optimization protocols incorporating predictive tools in ProteinQure platform
• Present our work at major conferences and to customers