Postdoc Fellow

Job summary

Lead or contribute to research projects analyzing population mental health outcomes, including predicting disease trajectories and deep phenotyping patients with complex diseases. Develop and communicate research findings through manuscripts, presentations, analytic methods, collaboration with research teams and local partners, and grant applications.

Job details

Post-Doctoral Research Fellowship at the Interdisciplinary School of Health Sciences, at the University of Ottawa The Interdisciplinary School of Health Sciences at the University of Ottawa is offering a post-doctoral fellow to work on a series of data analytical projects on population mental health outcomes. We are seeking to investigate methods to learn from longitudinal, multimodal data present in various data resources to: (1) predict disease trajectories and outcomes of patients with physical diseases comorbid with mental disorders; (2) perform deep phenotyping of patients with complex diseases, with the goal of improving diagnosis and treatment of these diseases. The research will also address the challenges in applying advanced statistics as well as machine learning methods to small datasets as well as the trustworthiness of machine learning and how we can improve the interpretability of machine learning models and their translatability to clinical care. The candidate will work in a multidisciplinary, highly collaborative scientific environment with opportunities to interact with other faculty members, clinicians, other computational researchers, as well as external collaborators. This position is for up to two years, with the possibility of renewal. What you will bring: (PhD, DrPH, or equivalent) or a related field confirmation of the doctoral degree (e.g., PhD, DrPh, SciD), or in final stage of doctoral program in statistics, computer science, epidemiology, sociology, psychology, mathematics; or a degree in biological science with demonstrated experience in computational and statistical methods development Advanced knowledge and proven track record in developing and applying statistical and/or machine learning methods to large real-world datasets Methodological expertise in cross-sectional and longitudinal analysis Experience in Stata/ R and Python for quantitative analyses is required. Advanced programming skills with familiarity of statistical software such as SAS and R Strong quantitative analytical and writing skills are required. Previous experience in social determinants of health, health and/or racial disparities, and populations at elevated risks of health outcomes is highly desired Strong written and interpersonal communication skills Ability to work independently and manage time effectively Ability to meet deadlines and work within budgets Advanced proficiency in English (spoken and written); French is an asset. Key responsibilities Lead or participate in research projects based on the Postdoc's background and interests May participate in the development of grant proposals, research protocols, surveillance plans, and analysis plans Prepares manuscripts detailing research findings and submits to peer-reviewed journals Participates in development of new analytic and data-sharing methods Presents research findings within and outside of the university Works closely with the research team to monitor progress and resolve issues that arise during the course of research Disseminate with local partners, and prepare grant applications to establish research independence. In keeping with our goal of training the next generation of strategic scientists, fellows will also be expected to pursue knowledge communication opportunities. Other duties and projects as assigned Application Applicants should provide the following application materials:1) a current curriculum vitae; 2) a 2- page cover letterhighlighting key qualifications, research interests, and experience; and 3) unofficial transcripts for undergraduate andgraduate degrees. Note: Official transcripts and three letters of reference will be requested if selected for a fellowship. Contact Questions about this position or requests for more detailed information can be directed to phds.research@uottawa.ca

What you’ll do

Lead or contribute to research projects analyzing population mental health outcomes, including predicting disease trajectories and deep phenotyping patients with complex diseases. Develop and communicate research findings through manuscripts, presentations, analytic methods, collaboration with research teams and local partners, and grant applications.

Requirements

Applicants must hold or be nearing completion of a doctoral degree in a relevant quantitative, health, or social science field, or have a biological science degree with demonstrated computational and statistical methods experience. Required qualifications include advanced statistical or machine-learning expertise, cross-sectional and longitudinal analysis, proficiency in R, Python, and Stata, strong quantitative and writing skills, and the ability to work independently; English proficiency is required and French is an asset.

Listed skills

• Data analysis · Preferred
• Machine learning · Preferred
• Communication · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Statistical Analysis
• Machine Learning
• Longitudinal Analysis
• Cross-Sectional Analysis
• Data Analysis
• Real-World Data
• R
• Python
• Stata
• SAS
• Advanced Programming
• Research Writing
• Communication
• Deep Phenotyping
• Clinical Research

Job areas

• Science & Research
• Data & Analytics
• Healthcare
• Education

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