Research Assistant 2 (Casual 0.0 FTE)

About the Program

Dr. Venkat Bhat’s research program, affiliated with the Interventional Psychiatry Division at The Royal, is currently looking for a Research Assistant II. The Interventional Psychiatry Division offers novel psychopharmacological (e.g. IV ketamine/other anesthetic agents), neurostimulation (e.g. rTMS, emerging neurostimulation modalities) and digital therapeutic (mobile-based monitoring and interventions) interventions for Mood and other Disorders. The interdisciplinary program offers emerging and procedural interventions for psychiatric disorders; the research program aims to understand treatment-response with these emerging interventions. In addition to Dr. Bhat, the Research Assistant II will have the opportunity to work with leading researchers in psychiatry, anesthesia, imaging, informatics and biomedical engineering. This position will focus on psychiatric clinical trials and digital mental health/artificial intelligence.

The Interventional Psychiatry Division is currently looking for a Research Assistant II. The primary role of the Research Assistant II includes contributing to the comprehensive research and development lifecycle — from fine-tuning small language models and building API-integrated pipelines, to conducting rigorous performance evaluations and co-authoring scientific manuscripts

Key Responsibilities

AI & Model Development

• Fine-tune small language models (SLMs) such as Phi, Gemma, Mistral, and LLaMA variants for mental health-specific tasks including symptom assessment, psychoeducation, and conversational support.
• Design and implement multi-step agentic workflows using frameworks such as LangChain and LangGraph.
• Integrate and orchestrate AI capabilities via API calls to foundation model providers (e.g., Anthropic, OpenAI, Google, Hugging Face Inference API).
• Develop prompt engineering strategies, retrieval-augmented generation (RAG) pipelines, guardrail, and tool-use patterns tailored to clinical and behavioural health contexts.

Performance Evaluation

• Design evaluation frameworks and benchmarks to assess model accuracy, safety, clinical relevance, and alignment with mental health guidelines (e.g., DSM-5, PHQ-9, GAD-7).
• Conduct red-teaming, bias audits, and hallucination assessments specific to mental health outputs.
• Implement A/B testing and continuous evaluation pipelines to track model performance over time.
• Document findings and translate results into actionable improvements for the engineering team.

Research & Manuscript Writing

• Contribute to the design and execution of research studies, including literature reviews, methodology development, and IRB/ethics documentation.
• Co-author peer-reviewed papers, conference submissions, and technical reports for PubMed indexed journals.
• Synthesize findings from experiments and translate them into clear, rigorous scientific prose.
• Maintain organized research logs, experiment tracking (e.g., MLflow, Weights & Biases), and reproducible code repositories.

Qualifications

• Bachelor's or Master's degree (or equivalent experience) in Computer Science, AI/ML, Biomedical Engineering, Cognitive Science, or a related field.
• TCPS CORE 2 is preferred (Must be completed within first 2 weeks of hire)
• Proficiency in Python and experience with ML/NLP libraries including PyTorch, Hugging Face Transformers, and PEFT/LoRA for fine-tuning.
• Demonstrated experience making API calls to LLM providers and building production-ready integrations.
• Familiarity with evaluation methodologies for generative AI, including automated metrics and human-in-the-loop assessments.
• Strong scientific writing ability with evidence of prior manuscript preparation, thesis writing, or published work.
• Ability to work independently, manage multiple concurrent tasks, and communicate findings clearly to both technical and non-technical stakeholders.

Valued Assets:

Cloud & DevOps

• Experience deploying ML workloads on cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with enterprise AI deployment practices including CI/CD pipelines, Docker/Kubernetes containerization, etc.
• Experience with MLOps tools for experiment tracking, model versioning, and automated retraining pipelines.
• Knowledge of data privacy and security requirements relevant to healthcare AI (PHIPA, PEDIPA, GDPR).

Mental Health, Psychology & Neurology

• Academic or professional background in clinical psychology, psychiatry, counseling, neuroscience, or public mental health.
• Familiarity with validated clinical instruments and psychometric scales (e.g., PHQ-9, GAD-7).
• Understanding of therapeutic modalities relevant to AI-assisted interventions (e.g., CBT, DBT, motivational interviewing).
• Experience with neuroimaging data, EEG/physiological signal processing, or digital phenotyping is a plus.
• Prior work in a clinical, research, or peer support setting within mental health or neurology contexts is highly valued.

Language Requirements

• English level A- is mandatory in oral expression, oral comprehension, reading comprehension and written expression. Bilingual (French/English) is preferred.