Post Doctoral Associate

Institution/Company:
Princess Margaret Cancer Centre
Location:
Toronto, ON, Canada
Job Type:
  • Postdoctoral
Degree Level Required:
PhD
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Post Doctoral Associate

The Kumar Lab at the Princess Margaret Cancer Centre and The University of Toronto is seeking a Postdoctoral Fellow to study cancer biology on the genetic and molecular levels by utilizing integrative computational approaches. Our research interests include developing and applying novel computational frameworks that leverage large-scale multi-omics and biomolecular structural data to identify clinically actionable cancer biomarkers and study tumor evolution. This position will offer ample opportunities to collaborate with a diverse group of clinicians, experimental and computational biologists at the Princess Margaret Cancer Center, University of Toronto, and beyond. This position will also provide abundant opportunities to mentor graduate and undergraduate students at the University of Toronto. Beyond research and mentoring experiences, the post-doctoral scientist will have opportunities to apply for various internal and external fellowships and grants to start their independent career.

Responsibilities:

Responsibilities:

Analyze large-scale biomolecular and sequencing data from major internal and external resources Develop novel statistical and machine learning-based methods and tools Collaborate with members in the lab and beyond to analyze and interpret biomolecular data, including sequencing, functional genomics, clinical, and biomolecular simulation data Contribute to the development and testing of data science workflows and implementations in high-performance and cloud computing environments Contribute toward maintenance of lab code base and software packages Mentor undergraduates and graduate students in the lab Publish and present results in peer reviewed journals and scientific conferences

Qualifications:

Qualifications:

PhD degree obtained within the last five (5) or MD within the last ten (10) years PhD in computational biology, computer science, statistics, or a related field Proficiency in at least one programming language (C/C++, R, Python) Experience working in a Unix-based environment Prior experience in analyzing next-generation sequencing data, machine learning, and biostatistics is preferred Prior experience in working on high-performance clusters or cloud computing environments is preferred Prior publication record with at least two first author (including join first) papers/preprints Excellent organizational and analytical skills and a high degree of independence and flexibility to thrive in a novel and rapidly evolving research environment Track record of teaching and mentoring students Ability to communicate and work effectively with a diverse team of clinicians and scientists, including post-docs, students, and staff members