We have an exciting opportunity to join our team as a Research Engineer.
The goal of the research project is to build new computer disease simulation models for pre-cancers and cancers, using state-transition microsimulation. The role will entail applying model inputs from national registries and large datasets for incidence and mortality data and the literature, and programming the disease model (using python and R). The research engineer will require comprehension of basic epidemiologic and disease-related terminology, and some experience with writing original manuscripts. Regular presentation of updates and findings we will occur through oral and written communication with the Principal Investigator and the research team.
- Design and encode disease simulation model, working together with the Principal Investigator.
- Understand the basic principles of diagnostic test accuracy measures and receiver-operating characteristic curves; apply economic evaluation.
- Regularly meet and communicate the status of the project, results, and finding.
- Create database of results and lead data visualization.
- Participate in preparation of manuscripts and presentations as needed according to the results.
To qualify you must have a Preferably PhD in decision science, systems engineering, mathematics, computer science, or related field; for an experienced researcher a Masters degree in field of public health or closely related area may be sufficient.
Familiarity with Markov models, Monte carlo simulation, basic probability theory.
Ability to conduct literature searches using standard medical databases (e.g. pubmed/medline, embase)
Knowledge of statistics (at a minimum, multivariable regression and probability theory, and ideally with ability to perform time-to-event analysis) and epidemiology, proven by successful completion of related coursework or research experience
Communication with medical students, faculty and/or staff in a team environment
Ability to communicate scientific concepts as described in the project summary, orally and in writing
strong skills in programming, ideally experience in cancer or other disease simulation modeling; 2) strong understanding of basic statistical analysis and ability to use a standard statistical package, 3) fluency in basic epidemiology and its terminology; 4) ability to conduct systematic literature searches, and 5) strong organizational skills for data management, as well as excellent verbal and written communication skills.