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University of Manitoba Postdoctoral Fellowship in Epidemiology, Canada
Dr. Tracie Afifi at the University of Manitoba, seeks a postdoctoral fellow who will conduct research on the effects of child maltreatment and other adversity on mental health, physical health, and educational, social and justice outcomes. Dr. Afifi is an Associate Professor in the Departments of Community Health Sciences and Psychiatry. This position has a one-year term, but can be extended for up to one additional year subject to availability of funding and satisfactory performance evaluations.
Dr. Afifi is currently conducting a primary data collection to learn more about thehealth, wellbeing, and experiences of adolescents, parents, and families in Manitoba. The goal of this project is to improve health and well-being for adolescents and their families by learning about their positive and adverse experiences and how they relate to mental health, physical health and education, social, and justice outcomes. The baseline data collection is currently underway. Our goal is to collect data on 1,000 adolescents aged 14 to 17 years old, paired with 1,000 parents or caregivers. We will be linking these data to the administrative data housed at the Manitoba Centre for Health Policy ( MCHP ).
The successful candidate will lead the all aspects required to link the survey data to the administrative data house at MCHP including all ethics and approval procedures. He / she will also lead statistical data analyses of the linked survey and administrative data. Data analysis opportunities will also be available for analyzing the survey data ( not linked ) as well as secondary data analysis using other data sources related to child maltreatment projects that are ongoing in the lab. This will include data analyses of data housed at our lab and Statistics Canada data housed at the Manitoba Research Data Centre ( RDC ). The successful candidate will also participate in the planning and implementation of the second wave of data collection for this cohort as well as other new data collection opportunities that may arise. In addition, the successful candidate will be responsible for knowledge translation and dissemination activities related to this work.
The successful candidate will have completed, or be near completion of a PhD in epidemiology, Community Health Sciences, or related field with completion of the PhD prior to appointment. Excellent oral and written communication skills are required. Excellent quantitative data analytic skills are required with proficiency in SPSS, STATA, and / or SAS. The successful candidate should have a good publication record and will be expected to apply for external funding during the term of this position, such as Research Manitoba Postdoctoral Fellowship.
To apply, send a cover letter summarizing your qualifications and research interests, a CV in PDF format, transcript, an English reprint of your most significant publication of research paper, proof of proficiency in English for candidates whose native language is not English, and contact information for three references to email@example.com. All applicants are thanked in advance; only those selected for further consideration will receive a response. Review of applications will begin on 1st October, 2017. Expected start date for this position is 8th January, 2018.
The University of Manitoba is strongly committed to equity and diversity within its community and especially welcomes applications from women, members of racialized communities, Indigenous persons, persons with disabilities, persons of all sexual orientations and genders, and others who may contribute to the further diversification of ideas. All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority.
Application materials, including letters of reference, will be handled in accordance with the protection of privacy provision of The Freedom of Information and Protection of Privacy ( Manitoba ). Please note that curriculum vitae may be provided to participating members of the search process.