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Job Location | Calgary, AB |
Education | Not Mentioned |
Salary | Not Disclosed |
Industry | Not Mentioned |
Functional Area | Not Mentioned |
Job Type | Full Time |
Position DescriptionArea: Cancer GenomicsDuration: 2 years, with potential for extensionStart Date: Position available immediately, start date negotiableSalary: $50,000/year plus benefits - negotiable based on qualifications and experienceThe Morrissy and Monument Labs are jointly seeking an outstanding scientist to join our team in the Cumming School of Medicine at the University of Calgary is a Postdoctoral Scholar in Computational Cancer Genomics.Successful candidates will be PhD graduates who are interested in making fundamental discoveries in tumor evolution and immune response that can lead to translational impact in aggressive and largely incurable subtypes of sarcoma.Research approaches in our team include multi-omic profiling of tumor samples at the bulk and single cell level, paired with functional genomics, mouse modeling, and translational mouse-hospital approaches. The project has a direct connection to the clinic and utilizes bio-banked material as well as prospectively collected sarcoma patient samples. We are particularly interested in the interplay between tumor cells and immune response, and what role the immune microenvironment plays in recurrent and metastatic disease. Understanding the molecular basis of tumor evolution after standard therapy could result in rapid clinical translation of novel therapies.We are part of a multi-disciplinary team of cancer researchers filled with passionate and determined individuals who will provide the successful candidate with a stimulating and conducive environment to participate and grow as a scientist. The research is conducted at the University of Calgary, in close collaboration with local and international scientists and clinicians, and thus will also provide the successful candidate with opportunities to learn from a large network of talented professionals.Responsibilities:The Postdoctoral Scholar will lead integrative analyses of multi-dimensional cancer genomics data from patient samples with rich clinical annotations, and from mouse models of the disease. The candidate will use statistical and machine learning approaches to interpret data (genomic/proteomic and spatial transcriptome datasets) in the context of tumour evolution, with the aim of understanding the dynamics of tumour growth, relapse, metastases and progression. The candidate will design and carry out experiments and lead the writing of scientific manuscripts.Qualifications:The successful candidate should hold a PhD completed within the last 3 years, have a track record of creativity in developing analytic strategies, and a strong foundation of knowledge in one or more of the following: genomics, cancer biology, statistics, immunology.Practical experience with bioinformatics, biostatistics, genome analysis, next-generation genome data management and analysis, Unix, Python, R & Bioconductor is highly desirable. Must be self-motivated, have strong written and verbal communication skills in English, and evidence of scientific accomplishment via peer-reviewed publications.