University Health Network (UHN) is looking for an experienced professional to fill the key role of Postdoctoral Fellow in our Research Department.
Transforming lives and communities through excellence in care, discovery and learning.
The University Health Network, where “above all else the needs of patients come first”, encompasses Toronto Rehabilitation Institute, Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre and the Michener Institute of Education at UHN. 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.
University Health Network (UHN) is a research hospital affiliated with the University of Toronto and a member of the Toronto Academic Health Science Network. The scope of research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. Research across UHN’s five research institutes spans the full spectrum of diseases and disciplines, including cancer, cardiovascular sciences, transplantation, neural and sensory sciences, musculoskeletal health, rehabilitation sciences, and community and population health. Find out about our purpose, values and principles here.
The Ailles Lab uses primary tumor tissues and patient-derived models of cancer to understand cancer biology and develop personalized approaches to cancer therapy. The Haibe-Kains Lab focuses on developing novel machine learning approaches for biomarker discovery from large pharmacogenomic data. We seek a postdoctoral fellow to participate in multiple projects to identify novel prognostic and predictive biomarkers, interactions between cancer cells and their microenvironment, and identification of novel therapeutic targets. Bioinformatic analysis and novel integrative approaches of multi-omic data sets, including RNAseq, single-cell RNAseq, proteomics, whole-exome sequencing, ATAC-seq, and Cut’N’Run data sets, will be required. The candidate will be co-supervised by Drs. Laurie Ailles and Benjamin Haibe-Kains.
Dr. Ailles’ lab will host the candidate. Dr. Ailles has over 15 years of experience in stem cell and cancer biology. Areas of research include cancer stem cells, cancer-associated fibroblasts, clonal heterogeneity and epigenetics. Our research utilizes primary patient-derived cancer tissue specimens, as well as patient-derived primary cultures and xenografts. Diseases studied include head and neck squamous cell carcinoma, high-grade serous ovarian cancer and clear cell renal cell carcinoma. We have established a “living biobank” of patient-derived xenografts that can be used to assay cancer stem cells, evaluate drug responses and development of drug resistance, and to perform a wide range of novel, clinically relevant studies. We collaborate extensively with other labs, clinicians and clinician scientists. Future studies will include extensive genomic and proteomic profiling of patient tissues and patient-derived model systems. For an exhaustive list of publications, go to Dr. Ailles’ Google Scholar Profile
The candidate will be co-supervised by Dr. Haibe-Kains, who 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.
- Recent completion of PhD (within five (5) years) in computational biology, computer science, statistics, or applied mathematics or related discipline
- 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.
- Strong expertise in programming and machine learning (R, Python, C/C++ and Unix programming environments).
- Hands-on experience in high performance computing, especially for parallelizing code in R and/or Python in a cluster environment (e.g., Slurm, commercial cloud platforms). Some background in biology/wet-lab research would be an asset
- Exceptional organizational skills and team-work ethic
- Capable of multitasking with minimal direct supervision
Vaccines (COVID-19 and others) are a requirement of the job unless you have an exemption on a medical ground pursuant to the Ontario Human Rights Code.
If you are interested in making your contribution at UHN, please apply on-line. You will be asked to copy and paste as well as attach your resume and covering letter. You will also be required to complete some initial screening questions
Posted Date: January 13, 2022 Closing Date: Until Filled
More information and apply here.