Summary of position

We are seeking a highly motivated and qualified individual to join our dynamic team at the Centre of Excellence in Youth Mental Health (CEYMH), located at the Douglas Mental Health University Institute. Through a combination of innovation in health service delivery and research focused on new interventions, the CEYMH is a hub for transformative change for youth facing a variety of needs – health, social, educational, employment, among others. The Centre focuses not only on research to generate new knowledge, but to directly applying such knowledge in the delivery of youth mental health services and providing training to a new generation of clinicians, researchers, and individuals with expertise by lived experience.

The Summer Research Assistant will work on the ongoing MOTS+ project, focusing on speech and language data in relation to symptoms and cognition in schizophrenia. They will extract baseline MOTS data, set up structured data forms with a clear legend, and integrate speech and language measures with REDCap clinical data. The RA will also contribute to refining a scientific question that explores the relationship between language patterns, psychiatric symptoms, and cognitive function. Throughout the project, they will gain experience in data management, interdisciplinary collaboration, and clinical research applications. The RA may also help with ongoing duties for the MOTS+ study in London, ON.

Dr. Alban Voppel, Postdoctoral Fellow, and Dr. Lena Palaniyappan, the co-supervisors for this position, are very involved in their research and will be providing supervision and feedback.

Description of tasks

• Code preparation and documentation;
• updating large databases;
• setup and execution of machine learning and computational models;
• general code stewardship;
• creation of data analysis pipelines;
• may occasionally contribute to analysis of multimodal data including language, questionnaire, clinical and acoustic data;
• may occasionally contribute to presentations and generating data visualizations.

Required qualifications

• Bachelor’s in related field (e.g., computer science, data science, computational neuroscience)
• Practical experience working with computational models or machine learning/AI models

Required skills

• Familiarity with key programming languages and environments (e.g., Python, Jupyter Notebook) for machine learning
• Familiarity with word processing programs, Excel
• Familiarity with team management and communication software (e.g. Microsoft Teams, Outlook, SharePoint, Slack)

Required abilities

• Ability to take initiative, be proactive, engage and take ownership of tasks
• Excellent interpersonal, written, and verbal communication skills
• Willingness to properly comment code and experiments
• Demonstrated capacity to work in a multidisciplinary team in a fast-paced, result-oriented environment

Location of work

Remote.

Work schedule

• Part time (14-21 hours a week)
• 4-month contract, renewable upon satisfactory progress

Salary

$18/hour

Required to travel?

No

Instructions for submitting an application

Send your CV to the hiring team at info@ceymh-cesmj.ca Please ensure your application explains how your background meets the listed requirements for the position.

Thank you for your interest in this opportunity. Kindly note that only qualified applicants will be contacted.

 The Centre of Excellence in Youth Mental Health hires on the basis of merit and is strongly committed to equity and diversity within its community. We welcome applications from racialized persons, visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities.

E-mail

info@ceymh-cesmj.ca

Name of immediate supervisor

Dr. Lena Palaniyappan, Director of the Douglas Centre of Excellence in Youth Mental Health.

Under direct supervision of Dr. Alban Voppel, Postdoctoral Fellow.

Posting dates

to