Jobs

Professor Yue Li is hiring one Postdoc for the machine learning and AI research in healthcare. The position will be held at the School of Computer Science.

The broad adoption of electronic health records (EHR) systems has created rich digital healthcare data and opportunities for conducting transformative health informatics research. However, irregular patient visits, heterogeneous data modalities, restricted EHR data access, and data distribution shifts among hospitals hinder their full utility. Rapidly advancing machine learning (ML) research offer great promise including transformer-based deep generative models and federated learning framework.

In Li lab, we develop explainable AI (xAI) methods that adapt the state-of-the-art AI methods for real-world life science applications pertinent to human health. In a funded project, we proposed 3 aims:

Aim 1: Predicting patient health trajectories using AI. Through our collaboration with the co-PIs at the McGill University Health Centre (MUHC), we have access to irregular longitudinal patient records for over one million patients from Montreal metropolitan area. We will develop a foundational “HealthGPT” model with a focus on predicting future health trajectories of patients by learning the hidden clinical semantics from pretraining on the massive EHR data. We will adapt the recently developed time-series transformer architectures to effectively account for the unequally spaced time-series time in our EHR data.

Aim 2: Robust federated learning in healthcare sectors. Training large neural networks to learn clinical semantics requires big data. Through our extended network, we can gain secure access to patient data on-site beyond MUHC. By using federated learning (FL) framework, we can aggregate model parameters in a central server without sharing the patient data from each hospital. To build a robust FL model, we will tackle data distribution shifts or out-of-distribution (OOD) challenges among hospitals. We will use deep density estimators to model the distributions within health centres and train OOD-aware AI models that are tailored to each hospital in their prediction tasks while harnessing the information across hospitals.

Aim 3: building real-world deployable software healthcare system for federated learning. While many FL algorithms in healthcare were developed, very few have been deployed in the real-world healthcare systems. This aim addresses the software engineering problem in building secure, robust, and efficient network communications between hospitals to deploy state-of-the-art AI methods in the health systems using/adapting existing FL frameworks such as Flower (https://flower.dev/).

Name of the immediate Supervisor:           Yue Li

Work schedule:         Five working days (Monday through Friday)

Working hours:         40 hours per week, 9 a.m. to 5 p.m.

Work location:           Trottier building at McGill Downtown campus

Salary information:   50,000 / year + benefits

 Planned start and end dates of appointment (if applicable):

The position can start on September 1, 2023, and ends on September 1, 2024. The position can be extended by 1 year.

To apply:  Send your CV and cover letter to : yueli@cs.mcgill.ca

JOB TITLE: Post-Doctoral Fellow in Computational Cancer Biology

Job Posting #: 924521

Site: Princess Margaret Research Institute

Department: Princess Margaret Cancer Center Living Biobank (PMLB)

Reports to: Principal Investigator

Hours: 37.5

Salary: $60,000 – 75,000: To commensurate with experience and consistent with UHN compensation policy

Status: Temporary Full-time (1 Year; with possible extension)

Posted Date: September 16,2023

Closing Date: December 1, 2023

The University Health Network, where “above all else the needs of patients come first”, encompasses Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute and the Michener Institute of Education. The breadth of research, the complexity of the cases treated, and the magnitude of its educational enterprise has made UHN a national and international resource for patient care, research and education. With a long tradition of ground breaking firsts and a purpose of “Transforming lives and communities through excellence in care, discovery and learning”, the University Health Network (UHN), Canada’s largest research teaching hospital, brings together over 16,000 employees, more than 1,200 physicians, 8,000+ students, and many volunteers. UHN is a caring, creative place where amazing people are amazing the world.

Position Summary

The PM Living Biobank is headed by Dr. Ming-Sound Tsao, who has over 30 years of experience in cancer pathology. He is the (co-)author of more than 600 peer-reviewed articles in top epigenomic, biology and clinical journals. For an exhaustive list of publications, go to Dr. Tsao’s Google Scholar Profile. Dr. Haibe-Kains has over 15 years of experience in computational analysis of genomic and transcriptomic data, in the context of translational research. He is the (co-)author of more than 200 peer-reviewed articles in top bioinformatics and clinical journals. For an exhaustive list of publications, go to Dr. Haibe-Kains’ Google Scholar Profile. Dr. Lupien has over 20 years of experience in computational analysis of genomic and transcriptomic data, in the context of translational research. He is the (co-)author of more than 130 peer-reviewed articles in top epigenomic, biology and clinical journals. For an exhaustive list of publications, go to Dr. Lupien’s Google Scholar Profile.

The candidate will work in a large multidisciplinary team of 8 laboratories from the Princess Margaret Cancer Centre as part of as part of Terry Fox New Frontiers Research Project:

• The PM Living Biobank: https://pmlivingbiobank.uhnresearch.ca/
• The Haibe-Kains Lab: https://www.bhklab.ca/
• The Lupien Lab: https://www.pmgenomics.ca/lupienlab/

Liquid biopsy technology development for early and non-invasive diagnosis of brain tumors

A postdoctoral position with a bioinformatics focus is available in the Molecular Oncology Laboratory of Dr. Dimitrios Mathios, MD, at The Brain Tumor Center of Washington University School of Medicine. Our laboratory aims to harness the expansive knowledge in brain cancer genomics, cancer epigenomics and immunogenomics to design liquid biopsy assays that will help us diagnose patients with brain tumors without the need for invasive surgeries. The goal of the lab is to take the liquid biopsy technologies developed in the lab and translate them to tests that can be used to guide patient care.

Working Conditions

This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals.

Salary Range

Base pay is commensurate with experience.

Applicant Special Instructions

Interested candidates should send a cover letter, their C.V. and a list of two or three references to mathios@wustl.edu.

Duties and Responsibilities

The Bioinformatician’s key role will be to develop and apply bioinformatics solutions to genomics research conducted by the TRIA-FoR project, a national scale, multidisciplinary network of researchers led by Carleton University and the University of Alberta. The bioinformatician will be located at Carleton University, and they will investigate resiliency and risk in the context of mountain pine beetle-climate interactions by linking genomics with quantitative genetics, population genetics, physiology, phenomics and spread risk modelling.