Term Adjunct Teaching Position Available
Posted on PHS Website: May 3, 2023

FOR FALL 2023 TERM
Department of Public Health Sciences

Course: MEDS 123 – Population Health

The School of Medicine at Queen’s University is seeking a Term Adjunct to teach Population Health (MEDS 123), a first-year course in the MD Program. This position is for one term, in-person instruction, commencing in September 2023 and concluding in December 2023, subject to funding and enrolment criteria.

MEDS 123 introduces students to the Canadian healthcare system and helps them to operate as leaders within it. The course explores issues in epidemiology at the population health level, including health promotion, screening, immunizations, disease outbreaks, surveillance, environmental and occupational health, interventions, and knowledge translation. Students will apply strategies and tools for health protection and promotion at the population level, and learn about theories and concepts for health behaviour change. The content from many aspects of this course form 'building blocks' for the rest of the MD Program Curriculum. It provides introductory content related to the following objectives from the Medical Council of Canada:

• Indigenous Health
• Administration of Population Health Programs
• Concepts of Health and its Determinants
• Environment
• Interventions at the Population Level
• Outbreak Management
• Preventative Health Encounter/Health Advice Sessions
• Work-Related Health Issues
• Disaster Preparedness, Emergency Response, and Recovery
• Assessing and Measuring Health Status at the Population Level

MEDS 123 is a three-unit, graduate course. The class is scheduled weekly, for 2-4 consecutive hours (varies on the week), for the duration of the 12-week term, for a total of 36 contact hours. The anticipated enrolment will be between 108-110 students.

Duties and Responsibilities

The successful candidate will be responsible for generating a course syllabus, incorporating existing course materials (on-line modules), compiling and distributing additional course materials as required, instructing weekly classes, communicating effectively with students, marking assignments, assigning grades, and providing on-campus or virtual office hours. Instructor will be responsible for teaching 100% of the course, although guest lecturers and visiting speakers are welcome.

Qualifications and Experience

Interested individuals are required to have a PhD in a Public Health-related discipline or a post-graduate degree with teaching experience in a related course.

Salary

In accordance with the Queen’s University Faculty Association collective agreement.

Application

It is asked that all interested and qualified candidates submit a complete and current curriculum vitae, a proposed course outline and the names and contact information for two referees who may be contacted.

Applicants are also invited to submit any other relevant material (e.g. teaching dossier).

Please email all documents to:

Dr. Bradley Stoner, Department Head
c/o Nikki Remillard
Department of Public Health Sciences
nikki.remillard@queensu.ca

Application deadline: Monday, June 19, 2023

Queen’s University is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, aboriginal people, persons with disabilities, and persons of any sexual orientation or gender identity. All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority.

Position: CANSSI Distinguished Post-Doctoral Fellow

Date posted: November 22, 2022
Department: Public Health Sciences

Description of Area or Topic of Research:

The successful applicant will be supported by funding from a Canadian Statistical Sciences Institute (CANSSI) distinguished postdoctoral fellowship and will work on a project entitled Development of innovative Bayesian methods to address statistical challenges in longitudinal electronic health record data. Specifically, the postdoctoral fellow will work on developing innovative, flexible, generalizable and interpretable Bayesian methods to analyze large and complex real-world clinical and public health data. The methodological contribution will focus on patient phenotyping and causal inference under longitudinal settings. This research also includes the development of accompanying software packages, open-access code, and tutorials to facilitate a wide application of the proposed methods.

More details regarding the research project and the training environment can be found here: https://incass.ca/wp-content/uploads/Development-of-innovative-Bayesian-methods-to-address-statistical-challenges-in-longitudinal-electronic-health-record-data.pdf 

Supervision and Academic Unit:

Dr. Zihang Lu (Primary supervisor, Biostatistics Program, Department of Public Health Science, Queen’s University)

Dr. Kuan Liu (Co-supervisor, Biostatistics Program, Dalla Lana School of Public Health, University of Toronto)

Dr. David Stephens (Mentor and collaborator, Department of Mathematics and Statistics, McGill University)

Salary: $70,000 per year
Start Date and Duration of Appointment: 2 years (24 months)

Required Qualifications:

• A doctoral degree in Biostatistics or Statistics
• Strong programming skill; Proficient in R, C++ and SAS.
• Knowledge of Bayesian statistical methods and modelling
• Strong communication, written and analytical skills
• Experience in collaborative research
• Ability to independently organize workload, set goals and work effectively towards deadlines
• Experience with analyzing clinical and public health data is an asset

Please apply through CANSSI website: https://canssi.ca/program/distinguished-postdoctoral-fellowships/.

Application Deadline: January 15, 2023

EMPLOYMENT EQUITY: The University invites applications from all qualified individuals.  Queen's is strongly committed to employment equity, diversity, and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous/Aboriginal people, women, persons with disabilities, and 2SLGBTQ+ persons.

ACCOMMODATION IN THE WORKPLACE: The University has policies in place to support its employees with disabilities, including an Accommodation in the Workplace Policy and a policy on the provision of job accommodations that take into account an employee's accessibility needs due to disability. The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes into account an applicant's accessibility needs. If you require accommodation during the interview process, please contact Zihang Lu at zihang.lu@queensu.ca or 613-533-6000, Extension 79336.

Position: Postdoctoral Fellow- Mobility (GPS) Research
Date posted: November 1, 2022

Site: Remote or Onsite (Queen’s University, Kingston, Ontario)
Department: Public Health Sciences
Reports to: Principal Investigator (Dr. Sahar Saeed)
Hours: 37.5 hours per week

Queen’s University is looking for an experienced professional to fill the key role of a Postdoctoral Fellow in our Public Health Sciences Department.

Are you a recent biostatistics or epidemiology Ph.D. graduate with experience analyzing aggregation data drawn from anonymous mobile data? We are looking for a postdoctoral fellow interested in building a career in data science.

Smartphones have become an essential part of our daily lives. Globally it is estimated there are 6.6 billion smartphone users, and by 2026 this is expected to increase to 7.5 billion. The unprecedented number of people with access to smartphones has created an opportunity to amass and track population-level mobility patterns through Global Positioning Systems (GPS). The COVID-19 pandemic exposed the capacity of using mobility data as an epidemiological surveillance tool to support public-health decision making. We are looking for a post-doctoral fellow interested in expanding on our team's mobility research which used aggregated location data to track the spread of SARS-CoV-2. You will lead projects that will identify disparities and evaluate the impact of the COVID-19 pandemic at long-term care facilities and hospitals. You will be working with a team of experts in epidemiology, biostatistics, geriatrics, and geospatial analytics and providing new insights on optimally leveraging anonymous mobility data that can continue to inform public health decision-making post-pandemic.

Job Description:

The post-doctoral fellow will work under the direction of the PI, but we encourage them to bring their own ideas and expertise. Candidates are expected to hold a Ph.D. from a recognized university. Candidates who are close to finishing their PhDs but have not published are also encouraged to apply. All candidates should have at least one manuscript published at the time of the application (illustrating advanced quantitative skillsets). The PI will encourage the fellow to use this fellowship (data/project) as a springboard to an independent academic career.

Qualifications:

• Recently graduate from a Ph.D. program in biostatistics, computer science or epidemiology (with a strong quantitative background) or equivalent (required)
• Expertise in R, Python or equivalent (required)
• Experience using location data or similar is required (candidates should include a brief summary of the data source they used, in their cover letter)
• An established track record in publications is an asset
• Excellent organizational and analytical skills, along with a high degree of independence and flexibility, to thrive in a novel and rapidly evolving research environment.
• Ability to write scientific communications
• Excellent initiative and leadership qualities

Salary: $50,000 per year Contract length: 12 months (starting January 2023).

Qualified candidates should send their CVs, transcripts and a cover letter indicating how they meet the job description to the PI (sahar.saeed@queensu.ca) by December 31st, 2022.

EMPLOYMENT EQUITY: The University invites applications from all qualified individuals.  Queen's is strongly committed to employment equity, diversity, and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous/Aboriginal people, women, persons with disabilities, and 2SLGBTQ+ persons.

ACCOMMODATION IN THE WORKPLACE: The University has policies in place to support its employees with disabilities, including an Accommodation in the Workplace Policy and a policy on the provision of job accommodations that take into account an employee's accessibility needs due to disability. The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes into account an applicant's accessibility needs. If you require accommodation during the interview process, please contact Sahar Saeed at sahar.saeed@queensu.ca.