Principal Researcher

• →Conducts collaborative research with faculty to be presented at academic forums and published in peer-reviewed academic journals.
• →Collects data and conducts statistical analysis.
• →Conducts literature reviews and perform research.
• →Leads system architecture decisions, model selection, and fine-tuning strategies for the CLARITY AI pipeline.
• →Designs and implements end-to-end integration of LLM-based text processing with video generation tools.
• →Develops guardrails to ensure factual accuracy, appropriate uncertainty communication, and clinical reliability.
• →Leads development of a secure, patient-facing interface that allows patients to access, review, and audit their personalized videos.
• →Collaborates with other staff and faculty on the CLARITY project.
• →Designs experiments to test prompting strategies and personalization features; analyzes experimental data.
• →Supports clinical trial development alongside medical faculty.
• →Uses subject matter and best practices knowledge to perform lab and/or research-related duties and tasks. Works independently to assist with project design.
• →Guides data collection, evaluation and analysis. Designs and manages databases. Writes reports, articles and manuscripts.
• →Performs other related work as needed.

• ABD status by start date, PhD preferred by start date in a field relevant to the research being conducted, such as computer science, artificial intelligence, machine learning, computational linguistics, or a closely related field.  PhD required after one year of employment.

• Demonstrated experience working with large language models (LLMs) and/or multimodal generative AI systems.
• Designing, implementing, and evaluating applied AI systems in real-world settings.
• Fine-tuning or adapting foundation models.
• Background with human-centered AI, AI alignment, or safety/guardrail design.
• Building user-facing AI systems or web-based interfaces.
• Working with healthcare data or other high-stakes domains.  

• Demonstrated ability to lead collaborative technical teams.
• Outstanding verbal, written, and presentation skills, as well as organizational skills.
• Work independently with little supervision; possess a self-motivated disposition; identify opportunities for improvement and recommend effective changes, all while achieving key objectives resulting in desired outcomes.
• Excellent strategic planning, critical thinking, analytical, and persuasion skills.
• Handle multiple detailed tasks/projects simultaneously and meet strict deadlines with frequent interruptions.
• Demonstrated ability to work effectively and diplomatically with colleagues, as well as with students, faculty and corporate contacts in a multitude of communication methods, including in person, email, and phone.
• Professional demeanor, including tact, discretion, and a customer service-oriented approach.

• This position is currently expected to work a minimum three days per week in the office.

• Resume/CV (required)
• Cover Letter (required)
• Two Letters of Reference, emailed directly to stephen.lamb@chicagobooth.edu (required)
• Academic Writing Sample (required)

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FLSA Status

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Pay Range

The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.

The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

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