Jobs

• Integrating Omics datatypes to build actionable models.
• Developing miRNA diagnostics using miRNA profiling from concordant peripheral and brain tissue profiles of highly phenotyped subjects using miRNA profiles from serum of phenotype subjects.

Project leverages:

• Whole genome sequencing of large cohorts of Alzheimer’s subjects.
• 4000+ subjects
• Resilience against AD pathology is a focus
• Modelling resilience to AD pathology against AD in 3D systems (R01 project)
• Determining single cell signatures of resilience to AD pathology with the CIRCUITS consortium
• Spatial transcriptomics, single cell nuclear RNAseq, miRNA and whole RNA assays of ‘extreme phenotype’ centenarian subjects who show resistance or resilience to AD
• Mapping the AD continuum using pathway activity signatures {AD GeneDex}
• using reference signatures for AD facets and predicting and testing interventions that perturb or enhance AD events

Job Reference Number: PDF_01553_Steif Lab_2022_05_16

We are currently looking for a Postdoctoral Fellow to join Dr. Adi Steif’s computational biology group.

The successful incumbent will lead the analysis of single cell data from a novel instrument, under development in collaboration with the groups of Dr. Karen Cheung (Biomedical Engineering) and Dr. Marco Marra (GSC / Medical Genetics). Funded by Genome BC, the project aims to improve the scalability and accuracy of cell isolation, in order to investigate tumour cellular diversity and evolution.

The position is anchored within a team of exceptional scientists, computational biologists and programmers, which collaborate directly on improving genome sequencing technology, interpretation and application. By working within the Steif Lab at the GSC, you will develop close relationships with world-renown specialists in bioinformatics and have access to one of the most robust computational and next generation genome sequencing technology facilities in Canada, all while living in one of the most beautiful, diverse and eclectic cities in the world.

This is an opportunity to work with highly motivated colleagues in a science-oriented, creative and dynamic environment. We offer a competitive salary, excellent benefits and significant career development opportunities.

A combination of engineered features and deep learning models will be used to extract and jointly analyze the imaging and genomic data. The first objective is to develop and evaluate novel computational imaging processing methods applied to multiple cancer types treated with chemotherapies, target therapies or immunotherapies. The second objective is to develop a cloud-based platform to facilitate the visualization and basic analysis of radiomics+genomics data in collaboration with the Software Engineers in the Haibe-Kains Laboratory (bhklab.ca).

This project (OCTANE 2.0) is funded by the Ontario Institute for Cancer Research and supported by Canexia Health. The candidate will be working in the Haibe-Kains Lab at the Princess Margaret Cancer Centre, University Health Network in collaboration with the Cancer Genomics Program and the Quantitative Imaging for Personalized Cancer Medicine, Techna Institute. A description of the project is available here.

The Division of Biostatistics and Computational Biology offers multidisciplinary work environment and a highly collaborative culture. The research projects include developing computational pipelines/algorithms for microbiome omics data integration and analysis. We develop and apply bioinformatics approaches to forge quantitative links between genetic, taxonomic, and functional aspects of microbial diversity and activities. Other research opportunities include bioinformatics development for oral cancer omics data integration and analysis to discover cancer genetic susceptibility. We develop and apply computational systems biology approaches to investigate the landscapes of genetic content in human oral cancer to identify molecular biomarkers for oral squamous cell carcinoma by mining and integrating patterns discovered from combined large data of bulk RNA-seq, single-cell RNA-seq, and epigenomics data. Other projects include biological ontology mining and network analysis for genotype-phenotype associations and electronic health record data mining on integrated dental patient data and general hospital data to improve decision making and personalized treatment, etc. The successful applicant will be under the supervision of Dr. Erliang Zeng, Associate Professor whose research is primarily in bioinformatics and data science, and Dr. Xian Jin Xie, Division Director and the Association Dean for Research for the College of Dentistry, whose research is primarily in biostatistics and bioinformatics. Both Drs. Xie and Zeng are affiliated faculty in the Department of Biostatistics of College of Public Health and the multidisciplinary Informatics Program.