Job:Postdoctoral Fellowship in Computational Cancer Biology at Princess Margaret Cancer Centre, Toronto
0
0
Entering edit mode
7.4 years ago

Postdoctoral Fellowship in Computational Cancer Biology: Translational Research in Lymphoid Malignancies @ Princess Margaret Cancer Centre (Toronto, Canada)

The Kridel lab is seeking a talented postdoctoral fellow to lead key research projects that are ongoing in the lab. The research will focus on one or more of the following topics: (i) analysis of next-generation sequencing data, including large-scale datasets, whole-genome sequencing data and epigenetic profiling; (ii) quantifying and modeling tumour evolution; (iii) statistical modeling of outcome following treatment. The PDF will design and carry out experiments to address key questions in the above topics and lead the writing of scientific manuscripts. Highly motivated individuals with a desire to make an impact in the field of cancer genomics are encouraged to apply.

For representative projects please consider the following references:

  1. Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study. Kridel R, Chan FC, Mottok A, ... Gascoyne RD, Shah P. PLOS Medicine. 2016 Dec 13;13(12):e1002197. PMID: 27959929.
  2. Integration of Gene Mutations Improves Risk Prognostication in Patients Receiving First-line Immunochemotherapy for Follicular Lymphoma in Clinical Trial and Population-Based Cohorts. Pastore A, Jurinovic V, Kridel R, Hoster E, ... Gascoyne RD, Weinstock DM, Weigert O. Lancet Oncol. 2015 Sep;16(9):1111-22. PMID: 26256760.
  3. Whole transcriptome sequencing reveals recurrent NOTCH1 mutations in mantle cell lymphoma. Kridel R, Meissner B, ... Weng AP, Steidl C, Gascoyne RD. Plenary Paper. Blood. 2012 Mar 1;119(9):1963-71. PMID: 22210878.

Required qualifications

The PDF should hold a PhD degree in bioinformatics, computer science, statistics or molecular biology and possess exceptional computational skills. Excellent communication skills are required, as is the willingness to work in a team environment.

Lab

We have an interest in B-cell lymphomas and are focusing on scenarios that are associated with poor outcome such as early progression after treatment, transformation to aggressive lymphoma and relapse in the central nervous system. We are applying cutting-edge tools to primary patient samples to unravel tumour heterogeneity and to develop novel, innovative biomarkers to predict outcome in lymphoma. Furthermore, we are leveraging novel findings from discovery platforms to elucidate mechanisms of lymphoma pathogenesis and treatment resistance. Our ultimate goal is to improve patient outcomes through a better understanding of the diversity of responses to treatment and by tailoring therapy to each individual patient. See our lab website for further information: https://kridel-lab.github.io/.

Princess Margaret Cancer Centre

The Princess Margaret Cancer Centre (PMCC) is one of the top 5 cancer centres in the world. PMCC is a teaching hospital within the University Health Network and affiliated with the University of Toronto, with the largest cancer research program in Canada. This rich working environment provides ample opportunities for collaboration and scientific exchange with a large community of clinical, genomics, computational biology and machine learning groups at the University of Toronto and associated institutions, such as the Ontario Institute of Cancer Research, Hospital for Sick Children and Donnelly Centre.

How to apply

Submit a CV, a copy of your most relevant paper, and the names, email addresses, and phone numbers of three references to robert.kridel@uhn.ca. The subject line of your email should start with "POSTDOC COMPBIO -- RKLAB". All documents should be provided in PDF.

next-gen lymphoma RNA-Seq subtyping • 1.9k views
ADD COMMENT

Login before adding your answer.

Traffic: 2699 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6