Job Description
The Krembil Centre for Neuroinformatics (KCNI) at the Centre for Addiction and Mental Health (CAMH) is harnessing the power of high-performance computing to integrate and analyze the wealth of data generated about the brain. Our research is performed in an open science environment, with an emphasis on reproducible data-driven research and a patient-centric approach to accelerate identification and treatment of mental illness. A focus on global collaboration is key to transforming our understanding of mental health and its treatment. The Centre operates as an incubator for medical technologies to identify, manage and treat mental illness, while shaping policy at national and global levels.
Position Description
The Whole Person and Population Modelling Lab, at the Krembil Centre for Neuroinformatics, has an opening for a full time, contract (1 year) Research Analyst. This position provides research support for the PI and the lab members. It offers the opportunity to be part of an active and productive team, and a dynamic Research Centre.
Primary responsibilities will include:
- Assisting with administrative tasks, including group meeting scheduling, trainee onboarding, lab website updates, and event planning.
- Becoming intimately familiar with major public and restricted-access research datasets used by the group (see lab website for details) and managing downloads and updates of these data, assisting with annual usage reports, requests for new data, and entering information/collecting signatures for data use agreements.
- Working with lab members to write and maintain high quality online documentation for computational/research tools and workflows used in the lab. This includes leading regular operations meetings to develop and improve our lab Github, Slack environment, and personalized learning plans.
- Communicating with and assisting team members, sometimes across institutions, in collaborative projects.
- Building in-house dashboards and working with the IT Operations team to streamline research data workflows (e.g. with Superset, dbeaver).
Secondary responsibilities and opportunities will include:
- Assisting in scientific report writing, including drafting grant proposals and publications.
- Performing statistical analyses on multimodal datasets to address important questions in mental health.
You will support a workplace that embraces diversity, encourages teamwork and complies with all applicable health and safety and regulatory and legislative requirements. This position is located at 250 College Street.
Job Requirements
The successful candidate will have a Bachelor’s Degree (e.g., Computer Science, Informatics Technology, Bioinformatics, Neuroscience) with 1 year of experience working in a research environment. The candidate will have 1) a solid understanding of data handling and fundamental biostatistics, including some previous work with population, cohort, or clinical datasets (experience with neurocognitive, MRI, or human genomic data types is an asset), 2) experience with computational tools including command line (linux, unix), version control, and cloud computing, 3) proficiency in R, Python, SQL, and other computing languages (experience with Confluence, Trello, Wix, Slack, and other web-based tools is a strong asset). Experience with regression, mixed models, principal component analysis, common machine learning models (lasso, ridge, elastic net regression, random forest, gradient boosted trees, neural networks), and data clustering methods is an asset but not required.
This position requires well-developed interpersonal and communication skills, as you will interact with a diverse set of stakeholders, researchers, students, organizations, and other support staff. You are a self-driven, highly detail-oriented and proactive worker with excellent organizational, problem-solving, and multi-tasking skills. You also demonstrate sound judgment, adaptability, and composure. You are flexible and willing to learn and adapt to different work assignments in a team setting, as well as work independently with minimal direct supervision. You value research and recognize the transformative impact it can make on patient’s lives. The successful candidate will support and implement anti-oppressive and anti-racist best practices in the workplace. The ability to work with stakeholders of diverse identities and ethno-racial and cultural backgrounds is required.
