06 Postdoctoral Fellowship at University of Toronto, Ontario, Canada

The BMO Financial Group Finance Research and Trading Lab (hereafter FRT-Lab), located on the 2nd floor of the Rotman School of Management, is an active learning centre that provides access to the global financial community and its resources in a real-time setting. The FRT-Lab houses a broad range of activities that enhance research, teaching, training, and global opportunities for the Rotman community.

We are seeking a research associate to provide support for our simulation-based-learning (SBL) products; in particular, to develop and maintain simulations that facilitate hands-on learning for financial decision making. Typical tasks could include:

• Programming simulations based on design specifications and input from other team members
• Preparing documentation and providing technical support associated with application of the simulations for education & training
• Evaluating output from applications to identify potential improvements in design and features
• Maintaining current knowledge of new developments in the field of financial modeling and simulation to identify possible improvements that could enhance our SBL products
• Development and improvement of portfolio back-testing and optimization tools.
• Support for development of decision cases and performance evaluation tools for our RIT Market Simulator platform. Existing RIT Decision Cases http://rit.rotman.utoronto.ca/cases.asp.
• Research support for data collection and analyses using our financial data platforms.

The Research Associate will work with the Director of Rotman FinHub and the Director of TDMDAL on building infrastructure needed to support research and teaching needs in analytics and machine learning. The RA will be responsible for managing and improving Rotman’s Python for Business instruction module for students and for building other infrastructure to support teaching and research needs in machine learning. This includes: devise and implement a plan to expand the current Rotman teaching modules to more students; provide consultations on research inquiries within Rotman on data analytics and different programming languages; provide end-user support for the Rotman teaching and research computing clusters; develop case studies; run programming workshops on the use of Python/R/Tableau etc. for data analytics; develop Python problem sets to be used in conjunction with Python workshops or other testable material to help students learning programming languages and applications in Python or other languages; assist with managing of data licenses and data storage within the school.

The Edward S. Rogers Sr. Department of Electrical & Computer Engineering is Canada’s top-ranked ECE department, and one of the largest. We are home to 100 active and Emeritus professors, more than 1,400 undergraduate and 600 graduate students. Many of our faculty members are world leaders in their field and have been recognized as the brightest and most promising scientists and engineers across the country. ECE is a hotbed of research commercialization, by far the most productive department for new inventions at the University of Toronto. In our department, you will work at the heart of the most rapidly developing technology humankind has ever seen.

Reporting to Dr. Sara Allin, the Research Associate will take a leadership role in a comparative analysis of health systems reforms and pandemic responses within and across Canadian provinces and with Australia, in partnership with collaborators across Canada and at the University of Sydney and University of Melbourne. 

The successful candidate will independently conduct research in the area of comparative health policy and also collate and analyze quantitative data; conduct qualitative interviews and perform qualitative analysis of interview data; summarize findings and play a lead role in manuscript and report preparation; engage diverse stakeholders; coordinate knowledge translation activities, such as round table dialogues and events; and supervise research assistants and/or work-study students.

The Research Associate is expected to independently carry out and conduct a research project to develop Artificial Intelligence (AI) and Machine Learning (ML) algorithms for data mining in the two research streams of the group: ultrafast electron diffraction and PIRL-DIVE-MS. More details about these projects can be found at  https://lphys.chem.utoronto.ca/research-overview/.