Postdoctoral Fellow – Generative AI for Mental Health

Postdoctoral Fellow – Generative AI for Mental Health

Global Center for AI in Mental Health (GCAIMH) University at Albany (SUNY) and SUNY Downstate Health Sciences University

Two-Year Fellowship

Position Summary

The

Global Center for AI in Mental Health (GCAIMH), a collaboration between the University at Albany and SUNY Downstate Health Sciences University, seeks an outstanding Postdoctoral Fellow in Generative Artificial Intelligence to advance innovative AI solutions that improve mental health access, quality, and outcomes at scale.

This position is funded through the Empire AI Postdoctoral Fellows Program and offers a unique opportunity to work at the intersection of artificial intelligence, mental health, global health, and public-good technology. Working closely with an interdisciplinary team of researchers, clinicians, computer scientists, and global health partners across SUNY institutions and international collaborators, the Fellow will contribute to the research, design, development, deployment, and evaluation of cutting-edge generative AI tools that support both frontline mental health interventions and evidence-based psychotherapy.

Research Focus

The Fellow will play a leading role in the development and evaluation of AI-powered initiatives for expanding access and equity in mental health, including but not limited to:

JulienPFA : An AI-supported implementation tool designed to strengthen Psychological First Aid (PFA) delivery during humanitarian crises, disasters, terrorism, and mass violence events. The system offers just-in-time guidance to non-specialist providers while supporting implementation fidelity, workforce development, and ethical learning systems.

TherAssist: A clinician-facing generative AI platform that supports psychotherapists delivering evidence-based treatments for anxiety and depression through real-time analysis, personalized treatment recommendations, and fidelity monitoring.

Responsibilities

The successful candidate will:

• Research, design, develop, and evaluate generative AI models for mental health applications.
• Deploy and use retrieval-augmented generation (RAG) to constrain large language models (LLMs) and multimodal AI systems.
• Conduct research using large-scale clinical, behavioral, and linguistic datasets.
• Utilize Empire AI computing resources for model training, evaluation, and deployment.
• Develop methods for responsible, ethical, and explainable AI in healthcare settings.
• Collaborate with clinicians, mental health researchers, software engineers, and data scientists.
• Publish findings in peer-reviewed journals and present at national and international conferences.
• Contribute to grant proposals and research dissemination activities.
• Mentor graduate and undergraduate students involved in AI and mental health research.
• Support partnerships with international collaborators focused on global mental health innovation.

Required Qualifications

• Ph.D. completed by start date, and not more than 5 years ago, in Computer Science, Artificial Intelligence, Machine Learning, Information Science, Data Science, Computational Neuroscience, Biomedical Informatics, or a closely related social science field with demonstrated skills and experience in computer science/artificial intelligence/machine learning.
• Demonstrated expertise with large language models, retrieval-augmented generation (RAG), agentic AI systems, and/or multimodal AI.
• Strong programming skills in Python and experience developing web-based AI applications with modern frameworks (e.g., Google Cloud Vertex, Gemini, CloudRun, Kubernetes, Firebase).
• Experience working with large datasets and high-performance computing environments.
• Strong publication record or evidence of research productivity.
• Excellent written and verbal communication skills, including the ability to communicate clearly and effectively about complicated scientific topics with a range of audiences.
• Ability to work effectively in interdisciplinary and collaborative research environments.

Preferred Qualifications

• Experience applying AI to healthcare, mental health, psychology, or social science domains.
• Familiarity with responsible AI, AI ethics, fairness, privacy, and safety considerations.
• Knowledge of natural language processing, speech analysis, or conversational AI systems.
• Experience working with clinical or healthcare data.

Research Environment …