HyperQuark Research Fellowship HQ-W27: Remote, Unpaid

**ABOUT THE FELLOWSHIP** HQ-W27 is the second cohort of the HyperQuark Research Fellowship, an unpaid, educational research programme run by HyperQuark Labs. It is remote and part time: twelve weeks from 4 January to 28 March 2027, about six to eight hours a week, with one weekly cohort session. About 12 fellows join, across four tracks. Its theme is evidence over claims: are the AI systems that read, match, grade and source people accurate, fair and reliable? Each track tests one new claim with open models on public, open-licence or synthetic data, to the standard of a publishable paper. **RESEARCH TRACKS** Judges You Can Trust: whether AI judges that agree with human graders on standard English still mark down the same answer written in Indian English. Fair Matching, India Edition: whether bias in AI résumé screening runs through caste-coded names or through proxies such as college tier, city tier and English variety. India Skills and AI-Exposure Graph: a validated map from India's occupation codes to skills, and whether India's own task descriptions change which jobs AI touches. Reliable Recruiting Agents: whether invented candidates and unsupported claims explain why sourcing agents that succeed once fail on later runs. **HOW IT RUNS** Twelve weeks in five phases: problem comprehension, direction lock, a quality gate at week 5, defence and validation, then write-up. A research pack opens each phase. Fellows share a short report each Sunday, and track leads answer it in writing. The hours are a guide, not a rule: you set your own schedule, it fits alongside study, and you may leave at any time. **WHO MAY APPLY** Enrolled students and independent researchers, aged 18 or over, who live in and take part from an eligible country. You do not need a PhD. India, Singapore and Japan: enrolled students and independent researchers South Korea: enrolled students aged 19 or over United States: enrolled students only, not resident in California or New York United Kingdom, Canada and Australia: only where your course requires the placement and your institution confirms it in writing Applicants from Germany, France, the rest of the European Union and Israel cannot join this cohort. **WHAT FELLOWS RECEIVE** Mentorship and written feedback on your work, access to the lab's studio and to compute for the fellowship, a certificate anyone can verify by its ID if you meet its requirements, and credit by name on what the lab publishes from your work. The fellowship is unpaid: there is no salary or other payment, now or later. It is not employment and not a route to a job. **DATA AND ETHICS** Public, open-licence or synthetic data only, open-weight models and published code Fellows never receive insiderOne product or user data, in any form No data collected from people, no scraping of people and no experiments on people **FELLOWSHIP AGREEMENT** Every fellow signs the HyperQuark Research Fellowship Agreement 2.0 before taking part. Under it, everything made in the fellowship belongs to Aurist Private Limited, which runs insiderOne and the lab. The company decides whether, what and when anything is published, and fellows are credited by name on what it publishes from their work. Taking part gives no claim, now or later, to payment, equity, a job or ownership. Read it before you apply: hyperquarklabs.insiderone.in/fellowship-agreement **WHO SHOULD APPLY** We look for curiosity, rigour and the ability to finish. Backgrounds in machine learning, natural language processing, statistics, economics and labour data, fairness and AI policy, or software engineering are all relevant. Applications close on 20 December 2026. More: hyperquarklabs.insiderone.in/fellowship