Scientific Associate - Krembil Centre Neuroinformatics

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Connected CAMH, to transform lives, ignite innovation and discovery, revolutionize education and drive social change. CAMH is more than a hospital, it is a cause. CAMH is on a mission to change the way society thinks about and responds to mental illness. They aim to eliminate prejudice and discrimination and shape a world where mental illness is central to our healthcare system – a world where Mental Health is Health.

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The Cognitive Network Modelling (Cog Ne Mo ) Lab at the Krembil Centre for Neuroinformatics (KCNI) within CAMH builds and applies computational models that infer subject-specific disturbances of information processing in neuronal circuits from behaviour, whole-brain neuroimaging, and electrophysiological measures, in order to address practical clinical questions in psychiatry. The lab focuses on characterizing disease states via symptom-relevant task and experiment design using multimodal imaging techniques.

All our work is conducted in a collaborative, open-science environment.

We are seeking a casual Scientific Associate with strong experience in computational modeling and clinical prediction research, spanning computational assays/digital biomarkers, measurement reliability and validity, and open-source analytical tool development, to support studies involving computational modelling and longitudinal neuroimaging pipelines.

The Scientific Associate will contribute to study execution and documentation, data analysis, and dissemination, including preparation of REB materials and study protocols, internal reports, conference presentations, and manuscripts for publication. The Scientific Associate may also support the supervision and mentorship of staff and research trainees as appropriate.

• Support study activities by contributing to REB submissions, study protocols, SOPs, and project documentation.
• Maintain clear documentation of analytic decisions, data handling procedures, and study workflows consistent with institutional standards and applicable regulatory requirements.
• Liaise with the PI and collaborators to ensure alignment on study procedures and deliverables.

• Support structured data collection, curation, and quality checks for longitudinal behavioral and neuroimaging measures.
• Apply appropriate analysis tools and methods to support computational modeling and clinical prediction objectives (e.g., statistical analyses, model evaluation, reliability/validity checks).
• Contribute to reproducible analytic workflows through organized code, version control practices, and clear documentation.
• Develop and evaluate computational models, including reinforcement learning, (hierarchical) Bayesian models, and active inference
• Apply advanced quantitative methods to connect model outputs to outcomes and mechanisms, including psychometrics (EFA/CFA, reliability, validity), multivariate statistics (CCA, PLS, dimensionality reduction), longitudinal modeling (mixed-effects models), and predictive modeling techniques (ML, cross-validation).
• Contribute to scientific publications, including drafting methods/results sections, preparing figures/tables, and supporting revisions.
• Prepare materials for conference presentations and other knowledge translation outputs (e.g., internal reports, posters, slide decks).

• Collaborate effectively with clinicians, scientists, trainees, and internal/external partners in a multidisciplinary environment.
• Provide day-to-day guidance and oversight to students or staff as needed (scope commensurate with experience and project needs).
• Maintain a respectful, inclusive work environment that embraces diversity and is free of harassment and discrimination.
• Experience gained during graduate studies or postdoctoral training, including conducting experiments, data collection and analysis, and research publication.
• Knowledge of the discipline, protocols, and regulatory requirements of the designated research area.
• A record of contributions to scientific publications.
• Demonstrated familiarity with analysis tools and methods relevant to the role, including programming in Python, R, and Matlab and quantitative modeling methods such as Bayesian modeling and/or reinforcement learning models, and psychometric/multivariate approaches (e.g., factor analysis (EFA/CFA), reliability/validity analysis, CCA/PLS).
• Evidence of open-science / open-source contributions (public repos, reusable tools, reproducible releases).
• Ability to collaborate effectively with colleagues and the scientific community.
• Demonstrated ability to interact with populations of diverse ethno-racial and cultural backgrounds.
• Experience supervising and overseeing staff and students preferred.
• Salary is…