Machine Learning 🚀 In Genomics 🧬 and HealTh ❤️ = 💡

Open positions

We are hiring postdocs, visiting scholars, and McGill undergraduate or graduate students interested in machine learning, computational biology or statistical genetics. Our research vision is to develop novel machine learning methods to decipher, in a human-understandable manner, the etiology of diverse phenotypes based on genetic variants, cell-type specificities, genomic regulatory elements, gene and pathway functions, and their interactions with environments. In this vision, we will develop deep generative models to

  1. account for the multi-modality of the heterogeneous data,
  2. impute correlated non-missing at random variables,
  3. infer latent trajectory of diverse patients' health states based on their longitudinal irregularly sampled outpatient data,
  4. infer the directed paths from driver genetic variants, causal genes and pathways, and to phenotypes leveraging the functional impacts of sequence mutations inferred from genomic data.

Interested postdoc applicants should:

The salary for a postdoctoral fellow will be based on the McGill University standards. Applicants should email their research summaries and three reference letters to Dr. Yue Li. Interested MSc/PhD students need to directly apply to the School of Computer Science at McGill University.

Emailing me if you are interested. To receive fast reply, please describe the following in your email: (1) Which of our papers (published after 2015 with me being either the first or last (co-)correspnoding author) that interest you the most? (2) Write a 1-2 page review on that or related paper; (3) Propose a project extended from that paper.