Scientific Advisor GEMINI Research (Job ID: 8861)
GEMINI (www.geminimedicine.ca) is a unique big data platform in the Canadian healthcare landscape using advanced methods and analytics to extract and standardize data captured in hospital electronic health records. GEMINI currently exists at 30+ ON hospitals and supports the Ontario General Medicine Quality Improvement Network, GeMQIN, a provincial network led by Ontario Health to improve care for general medicine hospital patients. General medicine patients represent 40% of emergency admissions to hospital and are the largest group of hospitalized patients. GEMINI is a collaborative data and analytics platform for all Ontario hospitals to accelerate research and quality improvement, leading to excellent hospital care.
We are looking for a highly motivated Scientific Advisor to join our team. The successful candidate will demonstrate outstanding critical thinking skills, strong background in statistical methods, data analytics and data visualization, as well as excellent scientific writing and research coordination skills. The Scientific Advisor will focus on leading grant writing, developing and coordinating project proposals, and working with the GEMINI Data Team to advance research methods. This is a full-time one-year position integrated within the GEMINI Data Team, working closely with a dynamic team of data analysts and scientists, clinicians and quality improvement specialists.
Duties and Responsibilities
Research (80%)
- Engage in grant funding opportunities when needed by providing strong understanding of GEMINI data holdings, GEMINI publications, and the most appropriate statistical methods
- Guide external collaborators at ICES in the planning, coordination, and execution of ICES projects using the GEMINI dataset
- Support idea generation and lead writing for grant funding submissions
- Manage competing priorities from different collaborators
- Support internal staff in the planning and coordination of research projects, conducting statistical analyses and interpretation of results
- Perform quantitative data analysis in collaboration with GEMINI data analysts while coordinating analyses with external organizations, where appropriate
- Lead and Assist in the development of manuscripts for publication in peer-reviewed journals, in consultation with Program Leads, Principal Investigators, the GEMINI team, and other research collaborators
- Chair research meetings as directed or required between GEMINI staff and external collaborators
- Prepare public presentations as needed
- Participate in project steering committees as needed
- Prepare protocols, project proposals and research ethics board applications
Managerial (20%)
- Participate in meetings, perform knowledge translation activities with the research team and research collaborators
- Provide guidance and direction to the Data Team staff on research projects
- Assist in setting research project goals and direction
Qualifications:
- Graduate degree, Master's required, PhD preferred in clinical epidemiology, mathematics, statistics, biostatistics, computer science, or a related discipline
- Demonstrated experience in leading large scale academic writing including research grants, academic publications, and research proposals
- Experience synthesizing comments and feedbacks from subject matter experts into a single cohesive piece of academic writing.
- At least 3 years of healthcare research experience or demonstrated equivalent combination of specialized education and relevant experience
- Advanced level experience with SQL and R
- Fully proficient in the use MS Office software (Word, Excel, PowerPoint, Outlook)
- Experience mentoring junior team members and provide guidance in each of the above-mentioned areas.
- Strong interpersonal, critical thinking and communication skills
- Excellent ability to analyze and problem solve in the areas of data management and preprocessing, modeling and evaluation
- Consult and lead the design and implementation of basic to advanced statistical and machine learning models using R libraries
- Advanced knowledge in inferential statistics and data science, working with large, messy datasets,
- Strong working knowledge of methods in observational clinical research.
- Experience preparing data for varied statistical methods preferred
- Experience with multiple study design formats preferred
- Experience with using high-performance computing environment is an asset
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