Postdoctoral Fellow-MSH-13400-376

Description of Research Project

This new initiative is focused on using behavioral measures and computational methods to define novel clinical signatures that can be used for individual-level prediction and clinical decision making in treating mental disorders. The importance of this new NIMH program was highlighted in a recent news update issued by the White House Office of Science and Technology. This study, titled, “Phenotypes REimagined to Define Clinical Treatment and Outcome Research (PREDiCTOR)”, will use objective, scalable, and cost-effective measurements to define novel clinical signatures that can be used for individual-level prediction and clinical decision-making in treating mental health disorders.

Technical Duties

• Research & Analysis: Conduct empirical studies in computational psychiatry, analyze multimodal datasets, and synthesize insights to support hypothesis-driven research and evidence-based treatment strategies.
• Machine Learning & Natural Language Processing Research: Develop and apply machine learning and natural language processing models to analyze textual, audio, and visual data to understand important clinical measures such as engagement, rehospitalization, and other clinical outcomes.
• Collaboration and Mentorship: Work collaboratively within an interdisciplinary team, and contribute to mentoring junior researchers, including graduate students and research assistants.

Qualifications

• Education: Ph.D. in Computer Science, Machine Learning, Data Science, Biomedical Informatics, Electrical Engineering, or a related field.
• Research Background: Demonstrated experience in one or more of the following areas: computational psychiatry, machine learning, and natural language processing.
• Technical Skills: Proficiency in programming languages such as Python or MATLAB, and experience with deep learning and natural language processing frameworks (e.g., TensorFlow, PyTorch) is highly desirable.
• Analytical Abilities: Excellent data analysis skills and familiarity with methodologies used in biomedical research.
• Communication Skills: Strong written and verbal communication skills, with a proven track record of research publications.