Research Associate

5 days ago


Toronto, Canada St. Michael's Hospital Full time

Our research lab in Mathematical Modeling for Program Science at the MAP Centre for Urban Health Solutions, St. Michael’s Hospital is recruiting a **Research Associate - Mathematical (Infectious Diseases) Modeler**. The focus and expertise for this position include mechanistic modeling of the transmission of infectious diseases in the context of sexual networks (in particular, syphilis, gonorrhea, chlamydia, monkeypox, HIV), Bayesian model fitting, simulating counterfactuals, and estimating comparative intervention impact. The research program is led by Dr. Sharmistha Mishra, and the CIHR and NIH-funded projects are conducted in close collaboration and partnership with scientists at Johns Hopkins University, University of Manitoba, BCCDC, UBC, McGill University, and ICES; and in close collaboration with community-based organizations and community scholars, public health program implementers, and policy-makers across jurisdictions.

The position involves leading a series of modeling projects on the sources and consequences of network-level heterogeneity on the emergence and persistence of infectious diseases in the context of sexual networks, and the comparative population-level impact of interventions. Opportunities also exist to provide input into surveys (primary data collection led by partners and collaborators) for model parameters and calibration/validation targets. The scope of work is integrated within a local, national, and global Program Science collaboration of clinicians, investigators, and policy-makers from multiple institutions.

The position will provide an opportunity to enhance advanced skills in simulation modeling and model fitting and will broaden knowledge and experience in the field of mathematical modeling for clinical and policy decision-making.

**RESPONSIBILITIES**
- Synthesize and analyze cross-sectional survey and cohort data, surveillance data, perform literature reviews, and parameterize and calibrate transmission models
- Develop analytic plans and work with statisticians and epidemiologists
- Lead, prepare, and disseminate modeling research and findings through presentations and peer-reviewed publications
- Communicate and liaise with research, policy, program, and community partners
- Mentor junior trainees
- Develop strategic partnerships with collaborators

**QUALIFICATIONS & EXPERIENCE**
- PhD in any of the following disciplines: Computational Biology, Ecology, Mathematical Modeling, Physics, Mathematics, Engineering, Computer Science, Biostatistics, Genetics & Molecular Biology, or related field - required
- At least 2 years of relevant experience in developing and coding disease/transmission models (compartmental and/or agent-based models), including experience with likelihood based model fitting - required
- High proficiency in at least 1 scripting language (R, Matlab, Python, etc.) - required
- Experience with building simulated networks - required
- Experience with manuscript and proposal writing - required
- Experience with phylogenetics - preferred
- Experience with Git/GitHub and LaTeX- preferred
- Experience with frequentist and Bayesian statistical inference - preferred
- Experience with statistical modeling - preferred
- Experience with causal inference - preferred
- Proficiency with high-performance computing, particularly via ComputeCanada - preferred
- Interest in using models to inform public health decision-making, and commitment to community-engagement in research
- Ability to work independently as well as part of a multi-disciplinary team
- Strong communications skills (oral and written) - technical and lay-language communication
- Excellent organizational, critical thinking, and problem-solving skills
- Ability to multi-task and prioritize tasks, and work accurately and effectively with deadlines (sometimes tight deadlines).
- Enjoy designing experiments via computer simulations, writing code, debugging, and writing papers
- Highly motivated and willing to self-learn new methods

**_


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