Jobs

Over the years, our team at University Health Network (UHN), University of Toronto, led by Sangeet Ghai, has developed methods for MR guided laser thermal therapy for localized prostate cancer. We propose treatment planning software that optimizes the ablation protocol for individual patients providing precise targeting of the tumor volume and improved preservation of surrounding healthy tissues. For future clinical trials, this requires a new tool to plan the placement of fiberoptics within the target tissue ensuring an optimal heating pattern. Topics of the postdoc’s research and daily work include:

• Implementation of software for generating optimal needle placement patterns, which must be adjustable by the clinician to account for interventional constraints
• Selecting suitable laser power parameters and modelling of the resulting regions of cell death
• Analysis of needle deflection data to identify an approach for deflection compensation or mitigation
• Detection and compensation for patient motion during the procedure
• Extending MR thermography software to provide robust, accurate, and reliable treatment monitoring
• Analyse the potential in reduction in treatment times
• Segmentation of anatomical structures and data analysis
• Experience in MRI would be advantageous
• Shadowing clinical procedures
• Writing manuscripts

Join our team as we integrate large-scale, genomic data and computational approaches to understand and predict psychiatric outcomes in clinical-treatment cohorts!

Applications are invited for a Postdoctoral Fellow position at the Pharmacogenetics Research Clinic at the Centre for Addiction and Mental Health and the University of Toronto, under the joint supervision of Dr. Daniel Mueller (M.D., Ph.D.) and Dr. Daniel Felsky (Ph.D.). The postdoctoral fellow will integrate psychiatric pharmacogenetics with various methods in computational biology and bioinformatics. Our primary goal is to understand and optimize the methodological opportunities and challenges for machine learning associated with the integration of genome-wide data from large-scale, epidemiological datasets and smaller, clinical-treatment cohorts. The postdoctoral fellow will engage in projects that aim to understand the genetic contributions to antidepressant non-remission in adults with depression and other psychiatric disorders within the context of underlying pathophysiology associated with aging and cerebrovascular and neurodegenerative changes.

To conduct data harmonization across multiple data-types including electronic health records, digital pathology, clinical notes and omics measurements (bulk and spatial) for patients undergoing heart transplantation. This position is strongly focused on method and software development related to 1) learning representations from multimodal data and 2) developing predictive models of rejection trajectories using multimodal data. Major responsibilities: 1) benchmarking existing methodologies for time-series data imputation, clustering and classification, 2) developing methods and software for the analysis of partially observed, multimodal time-series data, and 3) writing research proposals, reports and publications.

Land Acknowledgement
The University of Guelph resides on the treaty lands and territory of the Mississaugas of the Credit. We
recognize this gathering place where we work and learn is home to many past, present, and future First
Nations, Inuit, and Métis peoples. Our acknowledgement of the land is our declaration of our collective
responsibility to this place and its peoples’ histories, rights, and presence.

General Information (Six PDF Positions in Bioinformatics Available)
This post-doctoral position will be part of the Food from Thought initiative funded through a Canada
First Research Excellence Award: https://foodfromthought.ca/. Contributing to this large endeavour to
improve food security and sustainability, our goal is to generate bioinformatics strategies for the
prediction of biodiversity and ecosystem services from diverse data types, such as -omics data, digital
photographs, and/or environmental data. Data analysis has begun to catch up with the pace of data
generation, and in these times where understanding and mitigating the effects of climate change and
feeding a growing human population is of utmost importance, we need to turn our sights on connecting
different sources of data and extracting actionable meaning from them. The successful applicants will
utilize existing and new biological and environmental datasets, along with additional external data, with
the goal of predicting ecosystem services, ecosystem health status, and biodiversity metrics using
approaches such as statistical learning, machine learning, and network analysis. This may include such
important factors as pollination, invasive species resistance, pest control, trophic interactions, water
quality, and others. Successful applicants will be part of a cohort of six postdoctoral scholars focused on
bioinformatics and ecosystem services, who will work together with a multidisciplinary team of Principal
Investigators, students, staff, industry members, and communities.

What We Offer
• The opportunity to engage in creative and impactful research relevant for sustainability and
food security
• The opportunity to collaborate with researchers in a variety of fields, including computer
science, statistics, ecology, evolutionary biology, and genomics
• Guidance to build valuable skills and to be well prepared for diverse future careers (skills include
scientific research; collaboration; communication with diverse stakeholders; technical skills
relating to coding, data analysis, graphics, code review, and publishing of bioinformatics tools)
• Access to unique data sets and participation in collaborative partnerships with academics,
industry, and governmental agencies
• Regular, inclusive, and supportive mentorship from multiple PIs with diverse expertise to
support your research, career, and impact/outreach goals
• Participation in a collaborative working group of PDFs, workshops, and conferences
• Monetary support for professional development, workshop participation, and conference
attendance (up to $5000) as well as open-access publishing ($3000)

Please see the Job Responsiblities section for details on the specifics of each posting including responsibilities, requirements and instructions for applying. Please note that the date for commencing the review of applications varies among the six positions, as some were advertised earlier in other venues.

A computational postdoctoral position is available in the laboratory of Dr. Gregory Schwartz to study the role of cellular heterogeneity in cancer. The laboratory is located within the heart of the Discovery District, at the intersection of the Princess Margaret Cancer Centre, the University of Toronto, and MaRS, the center of a rich network of scientists and clinicians.

The laboratory studies the contribution of cellular heterogeneity to therapeutic response and cancer evolution. Towards this goal, the laboratory develops novel multi-omic and single-cell computational methods to improve cancer diagnosis and treatment through precision medicine. Notably, work from researchers in the laboratory include new methods for integration of transcriptomics and proteomics data to identify novel biomarkers across cancer subtypes, mutation detection tools characterizing new classes of internal tandem duplications, and clustering and visualization algorithms for single-cell transcriptomics and epigenomics. For more information on the types of tools we will develop, please visit https://schwartzlab-methods.github.io/.