Post Doctoral Fellow / cancer single cell biology
- University Health Network / Cancer Genomics Research Program
- Toronto, ON, Canada
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Post Doctoral Fellow / cancer single cell biology
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 groundbreaking 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.
Postdoctoral Fellowship in Cancer Single Cell -Omics
A postdoctoral fellowship is available in the laboratory of Dr. Trevor Pugh, PhD, FACMG at the Princess Margaret Cancer Center in Toronto, Canada (http://pughlab.org) . Located in the MaRS Centre in the heart of the downtown Discovery District, which is one of the fastest growing machine learning and big data analysis hubs in the world. We are an integral component of multiple translational genomics projects and platforms including the Cancer Genomics Program (www.cancergenomicsprogram.ca), Tumour Immunotherapy Program (www.pm-tumorimmunotherapyprogram.ca), PM Genomics Centre (www.pmgenomics.ca), and the Translational Genomics Laboratory, a joint initiative with the Ontario Institute for Cancer Research (https://labs.oicr.on.ca/translational-genomics-laboratory).
This newly-funded position will support a fellow wishing to lead collaborative, clinically-oriented cancer single cell genomic and transcriptomic analysis projects, with a focus on single cell transcriptomics methods development for cancer. This training opportunity is part of CReSCENT, the CanceR Single Cell ExpressioN Toolkit recently funded by Genome Canada .
This position is an opportunity for a scientifically creative, computationally-inclined individual with a strong background in one or more of the following areas: computational biology, mathematics, statistics, software development and machine learning. Previous experience in transcriptomics and/or cancer biology is a plus.
The fellow will gain experience integrating multiple types of next-generation sequencing data from single cell RNA-seq, genomics, and drug screening technologies. Key to these projects are training to interpret these data in the context of emerging new genomics technologies, algorithm and software development and implementation into an open source portal/toolkit.
Candidates must have a PhD with specialization in molecular genetics, bioinformatics, computer science or related fields, as well as hands-on experience in the use of Unix/Linux, R/Python, high performance computing, and statistical approaches to analyze and visualize genome-scale data sets. Preferred but not required are expertise in web and database development, software development practices (version control, etc.), and expertise using tools for analyzing single cell RNA-seq data such as Cell Ranger, Seurat, Scran, Monocle, etc. Candidates must be highly motivated, possess excellent organizational, problem-solving and communication skills (both verbal and written) and should have prior publications in one or more of the following fields: algorithms/software development, computational biology, cancer, genomics.
• A PhD degree in computational biology, bioinformatics, computer science, engineering, mathematics, or related disciplines is required • Working knowledge of Unix/Linux and strong programming skills (R/Python) • Practical experience with developing and applying statistics and/or machine learning algorithms • Multi-CPU and cloud programming experience are strong assets • Previous experience in bioinformatics is advantageous (high-throughput datasets, scalable graph analysis) • Experience analyzing scRNA-seq or gene expression data is beneficial • Good communication skills and the ability to work with an interdisciplinary team are essential