University Health Network
Degree Level Required:
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
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.
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:
We seek a postdoctoral fellow to mine and analyze the large-scale preclinical pharmacogenomic data generated by the Princess Margaret Cancer Center Living Biobank (PMLB) to identify new candidate drugs, targets and predictive biomarkers. The depth and multi-modality of these data will enable an unprecedented study of lung, breast, colorectal cancers and others to develop new treatment strategies and test them in patient-derived models such as organoids (in vitro) and mouse xenografts (in vivo).
The candidate will be hosted by the PMLB, Haibe-Kains and Lupien labs. The candidate will be responsible for aggregating the existing and future pharmacogenomic data and developing novel integrative approaches for the identification of molecular predictors of response to approved and experimental drugs.
The candidate will be assisted by software developers to leverage internal tools (PharmacoDB; PharmacoGx; XevaDB; Xeva) in order to develop a new cloud-based platform for the mining, visualization and analysis of preclinical pharmacogenomic data. Analytical approaches will span statistics, machine learning and artificial intelligence, which can be developed independently or in collaboration with other experts in the Haibe-Kains and Lupien labs and the greater Toronto AI community.
- Doctorate in computational biology, computer science, engineering, statistics, applied mathematics, or physics.
- Published/submitted papers in cancer genomics and/or machine learning research.
- Experience with analysis of high-throughput omics data, such as next-generation sequencing and gene expression microarrays, in cancer research.
- Experience with pharmacological profiling data (e.g., drug dose-response curves and tumour-growth curves) is an asset.
- Strong data engineering skills.
- Strong expertise in programming and machine learning (R, C/C++, Python and Unix programming environments).
- Hands-on experience in high performance computing, especially for parallelizing code in C/C++ (openMP) and/or R in a cluster or cloud environment
Applications must be submitted before December 1, 2023.
Why join UHN?
In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.
- Competitive offer packages
- Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
- Close access to Transit and UHN shuttle service
- A flexible work environment
- Opportunities for development and promotions within a large organization
- Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)
Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN’s attendance management program, to be eligible for consideration.
Vaccines (COVID and others) are a requirement of the job unless you have an exemption on a medical ground pursuant to the Ontario Human Rights Code.
UHN is a respectful, caring, and inclusive workplace. We are committed to championing accessibility, diversity and equal opportunity. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known in advance. Any information received related to an accommodation will be addressed confidentially.
University Health Network thanks all applicants, however, only those selected for an interview will be contacted.