Postdoctoral Research Fellow

The Division of Digital Psychiatry at Beth Israel Deaconess Medical Center (Harvard Medical School) is seeking a full-time Postdoctoral Research Fellow to help lead a newly funded, five-year NIH/NCCIH R01 clinical trial (R01AT013324, 2026-2031) studying mindfulness apps for depression.

The trial is a fully remote randomized controlled study testing whether matching participants to mindfulness apps based on the digital working alliance improves outcomes relative to a digital placebo, combining six weeks of prompted app use with six weeks of naturalistic follow-up. Smartphone-based digital phenotyping through the Division's open-source mindLAMP platform, including sleep, step count, screen time, time at home, greenspace exposure, and ecological momentary assessment, will be used to build personalized models of treatment response.

The fellow will join a multidisciplinary team of clinicians, researchers, engineers, data scientists, and people with lived experience, with protected time for first-author publications, career development, and preparation of independent funding (e.g., K awards).

• Serve in a leadership role in the day-to-day scientific conduct of the R01 trial, including protocol implementation, measurement fidelity, and data quality
• Analyze longitudinal digital phenotyping and ecological momentary assessment data to model engagement, symptom trajectories, and personalized treatment response
• Lead first-author manuscripts and support team publications, abstracts, and national conference presentations
• Contribute to study design decisions, statistical analysis plans, and NIH progress reporting
• Mentor research assistants and students supporting the trial
• Collaborate across the Division's related programs in digital interventions, engagement, and data science

• PhD, MD, or equivalent doctorate in clinical psychology, psychiatry, biostatistics, epidemiology, computational or translational science, or a related field
• Experience with clinical research; experience with randomized controlled trials or mHealth/remote studies strongly preferred
• Strong quantitative skills, including longitudinal or multilevel modeling, and proficiency in R or Python
• Demonstrated record of peer-reviewed publication
• Ability to work independently and collaboratively in a fast-paced translational research environment

• Digital phenotyping, passive sensing, wearable, or ecological momentary assessment data
• Mindfulness-based or other behavioral interventions for depression or anxiety
• Prediction modeling or machine learning with real-world longitudinal datasets
• Participant engagement, digital literacy, or digital working alliance research
• Interest in developing an independent research program and pursuing NIH career development (K) funding

• A central scientific role on a newly funded, five-year NIH R01 from its launch
• First-author publication opportunities and national conference presentations
• Mentorship from Dr. Torous and a team with more than 500 peer-reviewed publications
• Hands-on experience with mindLAMP, an open-source digital phenotyping platform used at more than 100 sites in 13 countries
• Grant-writing experience and structured support toward independent funding
• Exposure to the Division's broader portfolio spanning AI evaluation, digital clinics, and health policy

• Full-time position based at BIDMC in Boston, MA
• Two-year initial appointment expected, renewable based on performance and funding
• Salary commensurate with experience and NIH postdoctoral guidelines, with BIDMC/Harvard Medical School benefits
• Flexible start date, with a strong preference for Fall 2026; an August start is highly valued

The Division of Digital Psychiatry advances mental health care through smartphone-based digital phenotyping, digital therapeutics, AI safety evaluation, digital literacy initiatives, and technology-enhanced clinical programs, including the Digital Clinic model for depression and anxiety. The Division's work has informed Congress, the FDA, the UK MHRA, the WHO, and the American Psychiatric Association.

Learn more: docs.lamp.digital