"Postdoctoral Scholar in Computational Psychiatry and Digital Mental Health"

Position Title: Postdoctoral Scholar in Computational Psychiatry and Digital Mental Health

Location: Lebanon, New Hampshire

Department: Department of Biomedical Data Science

Position Type: Staff

Qualifications:

Required qualifications:

• Candidates must have an MD (e.g., be a psychiatrist) or a PhD in Clinical or Counseling Psychology by the start of the appointment.
• Demonstrated experience in suicide risk assessment and intervention.
• Candidates must be proficient in quantitative data analysis, as evidenced by a track record of publications and/or presentations.
• Candidates must have strong written and verbal communication skills.

Preferred qualifications:

• Experience analyzing ecological momentary assessment (EMA) and/or social media data using R and/or Python.
• Clinical or research experience in the fields of suicide, adolescent mental health, and/or computational psychiatry.
• Interest or experience in machine learning, natural language processing, or deep learning.
• In-person work at Dartmouth is preferred, but hybrid or remote-only applicants will be considered.

For more information regarding the AIM HIGH lab, please visit https://geiselmed.dartmouth.edu/jacobsonlab/.

Description:

The research team of Dr. Nicholas Jacobson, the AI and Mental Health: Innovation in Technology Guided Healthcare (AIM HIGH) Laboratory, is seeking a motivated postdoctoral scholar to join our dynamic and interdisciplinary team. Our lab leverages digital technology, computational modeling, and AI to improve the understanding, prediction, and prevention of mental health problems, with a particular emphasis on anxiety, depression, and suicide in adolescents and young adults.

The postdoctoral scholar will play a key role in a five-year, NIMH-funded R01 study titled "Suicide Transmission Dynamics on Social Media: Modeling Risk, Understanding Platform Differences, and Exploring Ethical Implications Among Young Adults". This project uses ecological momentary assessment (EMA) and social media data from 800 young adults to build and test deep learning models that predict rapid changes in suicidal thoughts and behaviors. A central responsibility of this position will be serving on the 24/7 on-call crisis response team, conducting clinical interviews to assess suicide risk, and managing participant safety according to the study's comprehensive safety plan.

The lab is housed within the Center for Technology and Behavioral Health (CTBH), a P30 "Center of Excellence" funded by the National Institute on Drug Abuse. The successful candidate will have opportunities for mentorship in digital health, advanced data analytic methods (e.g., deep learning, NLP, dynamic social network analysis), manuscript preparation, and grant writing. Opportunities for clinical hours and supervision toward licensure are also available.