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• Lead and contribute to the development, implementation, and execution of research projects related to sex and gender differences in brain health, mental health, aging, and neurodegenerative disease.
• Conduct secondary data analyses, including data management, harmonization, quality assessment, statistical modelling, and interpretation of complex health datasets.
• Apply epidemiological, clinical research, and data science methodologies to investigate biological, social, and environmental determinants of health outcomes.
• Integrate Sex- and Gender-Based Analysis Plus (SGBA+) principles into research design, analysis, interpretation, and knowledge translation activities.
• Prepare and contribute to scientific manuscripts, grant applications, research reports, presentations, and knowledge translation materials.
• Collaborate with multidisciplinary research teams, trainees, and external partners to support research initiatives and scientific communication.
• Mentor and provide guidance to trainees and research staff in research methods, data analysis, scientific writing, and professional development.
• Support responsible research practices through adherence to research ethics, data governance, privacy requirements, and reproducibility standards.
• Contribute to the strategic growth and advancement of the research program through collaborative research, funding initiatives, and dissemination of findings.

• A PhD in Epidemiology, Neuroscience, Psychology, Public Health, Health Sciences, Data Science, Biostatistics, Biomedical Sciences, or a related discipline.
• Minimum one (1) year of postdoctoral training in an academic, hospital, research institute, or equivalent research environment.
• Research experience in clinical research methods, epidemiology, health data science, women's health, neuropsychiatric research, aging, and/or related fields, with demonstrated experience leading complex research projects.
• Demonstrated expertise in secondary data analysis, including experience working with large-scale clinical, population-based, longitudinal, administrative, or biobank datasets.
• Demonstrated experience with data management, harmonization, quality assessment, variable development, statistical modelling, and interpretation of complex health datasets.
• Strong understanding of clinical research methodologies, epidemiological approaches, study design, and principles of responsible use of health data.
• Demonstrated expertise in statistical analysis and data visualization, with proficiency using analytical tools such as R, Python, SAS, Stata, SPSS, GraphPad Prism, or equivalent. Experience with Statistica is considered an asset.
• Strong knowledge and demonstrated application of Sex- and Gender-Based Analysis Plus (SGBA+) principles in research design, analytical frameworks, interpretation, and knowledge translation.
• Experience applying sex and gender considerations to health research, including the evaluation of biological, hormonal, social, and contextual factors influencing health outcomes.
• Experience analyzing data related to aging, menopause, neuroendocrine health, cognition, Alzheimer's disease, dementia, or other neurodegenerative conditions is strongly preferred.
• Strong record of scientific productivity, including peer-reviewed publications and demonstrated ability to prepare manuscripts, grant applications, scientific reports, presentations, and knowledge translation materials.
• Experience contributing to competitive research funding applications, including scientific strategy, proposal development, and collaborative grant submissions.
• Demonstrated experience mentoring undergraduate students, graduate students, postdoctoral researchers, and research staff, with the ability to provide guidance in research methods, data analysis, scientific writing, and professional development.
• Demonstrated ability to foster an inclusive, collaborative training environment that promotes critical thinking, scientific independence, and trainee development.
• Excellent organizational, leadership, communication, and project management skills, with the ability to manage multiple priorities and collaborate effectively with multidisciplinary teams.
• Knowledge of research ethics, privacy considerations, data governance frameworks, and responsible use of health data is required.
• Experience working with large-scale health datasets, electronic health records, population cohorts, multi-modal datasets, biomarkers, neuroimaging data, or predictive modelling approaches is considered an asset.

Compensation & Benefits:

• Salary is competitive and based on experience, with a hiring range of $93,822.73 – $117,278.41 per year.
• Employees in this role may progress within the full pay range of $93,822.73 – $140,734.09 per year
• CAMH’s Total Rewards : Includes participation in HOOPP defined benefit pension plan , flexible work arrangements, and ongoing professional development support.

This role allows professionals to apply their expertise in a mission-driven environment dedicated to public health outcomes.

CAMH is a fully affiliated teaching hospital and research institute of the University of Toronto. As a CAMH employee, you will contribute to our mission by supporting teaching, research, and clinical care across the hospital.

CAMH is dedicated to equity, diversity, and inclusion. Our commitment is to foster a workplace, teaching, and learning environment that is inclusive, respectful, and free from discrimination or harassment.

CAMH strongly encourages applications from candidates who reflect the diversity of the communities we serve, including First Nations, Métis, and Inuit Peoples; Black and other racialized communities; LGBTQ2S+ communities; women; and people with disabilities, including those with lived experience of mental health and substance use challenges.

We welcome applicants from all backgrounds. Thank you to all who apply; however, only those selected for an interview will be contacted. If you require accommodations during the application or recruitment process, please let us know.

CAMH est un hôpital universitaire et un institut de recherche pleinement affiliés à l'Université de Toronto. En tant qu'employé de CAMH, vous contribuerez à notre mission en soutenant l'enseignement, la recherche et les soins cliniques à travers l'hôpital.
CAMH est dédié à l'équité, à la diversité et à l'inclusion. Notre engagement est de favoriser un environnement de travail, d'enseignement et d'apprentissage qui soit inclusif, respectueux et exempt de discrimination ou de harcèlement.

CAMH encourage fortement les candidatures de candidats qui reflètent la diversité des communautés que nous servons, y compris les Premières Nations, les Métis et les Inuits; les communautés noires et autres communautés racialisées; les communautés LGBTQ2S+; les femmes; et les personnes en situation de handicap, y compris celles ayant une expérience vécue des défis en matière de santé mentale et d'usage de substances.

Nous accueillons les candidatures de toutes origines. Merci à tous ceux qui postulent ; cependant, seuls les candidats sélectionnés pour un entretien seront contactés. Si vous avez besoin d'aménagements pendant le processus de candidature ou de recrutement, veuillez nous en informer.