Postdoctoral Fellow in Myeloma Cancer Genomics and Immunogenomics

A postdoctoral fellowship is available in the laboratories of Dr. Suzanne Trudel, MSc, MD, FRCPC and Dr. Trevor Pugh, PhD, FACMG at the Princess Margaret Cancer Centre / University Health Network in Toronto, Canada. Located in the MaRS Centre in the heart of the downtown Discovery District, we are an integral component of multiple translational genomics projects and platforms including the Cancer Genomics Program, Tumour Immunotherapy Program, Princess Margaret Genomics Centre, and the OICR Genomics Program. This position is an opportunity for a scientifically creative, computationally-inclined individual with a strong cancer biology background to further their understanding of therapeutic response and resistance mechanisms to immunotherapy as well as underlying oncogenic mechanisms active in the hematologic malignancy multiple myeloma.

The fellow will gain experience integrating multiple types of next-generation sequencing data (single-cell multi-OMICs, targeted NGS panels, whole genome sequencing, and immune repertoire profiling), through analysis of tissue and blood collected serially from patients on a nation-wide immunotherapy drug trial. It is expected that this project will involve an in-depth correlative analysis of genomic data with clinical outcomes data to derive meaningful insight into therapeutic and disease mechanisms. Key to this project is training to interpret these data in the context of rich clinical annotations, new genomic technologies and computational approaches, especially in the emerging fields of single-cell multi-OMICs and whole genome sequencing. The successful candidate will gain experience working in an interdisciplinary team of computational and cancer biologists, and will collaborate with national research partners and industry sponsors.

Candidates must have a PhD or MD with specialization in genetics, molecular biology, bioinformatics, or computer science as well as hands-on experience in the use of R/RStudio, tools for analysis of next-generation sequencing (GATK, Picard suite of tools, and/or mutation detection algorithms) and single-cell sequencing data (Seurat, Scanpy, scran, and/or scater), and data visualization approaches for genome-scale data sets. Preferred but not required are experience in Unix/Linux, Python programming, high-performance computing infrastructure, version control practices, and familiarity with using public large-scale cancer and single-cell datasets. Candidates must be highly motivated, possess excellent organizational, problem-solving and communication skills (both verbal and written), and should have prior publications in cancer, genomics, immunology, and/or biomedical journals.