Clinical AI Research Lead

New
I
Insight TimerDigital Mental Health
The role is fully remote, but you must be based in Australia.Full-TimeLead
Salary not disclosed
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Job Details

Required Skills
Data AnalysisBehavioral sciencePrompt Engineering

Requirements

  • Strong clinical, psychological, behavioral science, or mental health research expertise.
  • PhD, candidate for PhD, or equivalent clinical and research experience.
  • Background as an academic researcher, clinician-researcher, psychologist, psychiatrist, or behavioral scientist.
  • Understanding of evidence evaluation, including study quality, validity, and real-world limitations.
  • Familiarity with meditation, mindfulness, psychotherapy, behavior change, or related wellbeing techniques.
  • Comfort working with ambiguity and complex, cross-disciplinary problems.
  • Willingness to work directly with AI prompts, model outputs, and evaluation systems.
  • Strong communication skills for interacting with engineers, product managers, designers, and non-clinical stakeholders.
  • Ability to distinguish between evidence-based, speculative, and risky content.

Responsibilities

  • Review and evaluate AI-generated outputs related to meditation, wellbeing, mental health, sleep, anxiety, stress, and behavior change.
  • Assess whether AI outputs are clinically appropriate, evidence-informed, safe, clear, and useful for real-world users.
  • Evaluate the strength and quality of evidence behind wellbeing, meditation, and psychotherapeutic techniques.
  • Help define frameworks for assessing indications, contraindications, risk, evidence quality, and real-world applicability.
  • Work with engineers and product teams to improve prompts, AI workflows, evaluations, and user-facing wellbeing experiences.
  • Translate clinical, psychological, and research concepts into clear product guidance.
  • Help build internal evaluation systems for AI outputs, including rubrics, review processes, and quality standards.
  • Collaborate with internal and external researchers on studies, evidence reviews, and potential peer-reviewed publications.
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