The Respiratory Evaluation Sciences Program (http://resp.core.ubc.ca) is looking for a highly motivated post-doctoral research fellow in the area of microsimulation modeling and predictive analytics. The candidate will be supervised by Dr. Mohsen Sadatsafavi, MD, PhD within UBC Faculty of Pharmaceutical Sciences.
This position will undertake several activities in either predictive analytic (clinical prediction modeling) or decision analysis (cost-effectiveness and epidemiological forecasting). Namely,
- Development and implementation of an agent-based simulation model for Chronic Obstructive Pulmonary Disease
- Creating, validating, and implementing prediction models that can predict heretogeneity of treatment effect
- Implementing Artificial Intelligence (AI) and Natural Language Processing (NLP) methods for facilitating the update of clinical prediction models
- Designing and implementing cloud-based technologies for remote access to clinical prediction models.
The candidate should have excellent quantitative skills. Activities under this project are generally on two fronts: advanced programming that relate to the implementation of disease simulation models, and statistical expertise in predictive analytics. Deep expertise in any of these two disciplines would be enough, with complementary skills in the other being an asset. Candidates with any background are welcome to apply as long as they can demonstrate they have the required skillset. Clinical and public health knowledge are asset.
RESP is embedded within Collaboration for Outcomes Research and Evaluation (CORE, http://core.ubc.ca), a growing academic unit bustling with productive students, thriving new investigators, and established senior faculty and mentors.
Preferred start date is negotiable and the position will remain open until July 1st 2021. The contracted term will be for one year, from which further extensions will be possible. If interested, please contact Mohsen Sadatsafavi (firstname.lastname@example.org) and supply a copy of your CV and up to one-page statement of interest.