NLP Research Fellow

## About the Role FairwAI is building the world's first bias accountability infrastructure — a compliance platform that detects systemic discrimination in real-world environments like healthcare. We're designing tools that surface bias in real time and hold institutions accountable. This is AI not as an optimizer, but as a watchdog for equity. If you are basic this isn't for you. This is for gamechangers! We're seeking a brilliant, mission-aligned NLP intern to join the team — our hospital equity analytics unit. You'll help us extract meaningful signals from real-world review data, such as: - Microaggressions and patient-reported discrimination - Health equity concerns (tone, treatment delay, misdiagnosis) - DEI failures and disparities across racial, gender, or disability lines You'll work closely with our founder, MIT & Harvard PhD's, and fairness technologists to prototype systems that go from reviews → labeled incidents. ## What You'll Do - Develop and test zero-shot and few-shot NLP models to flag bias, tone-policing, medical gaslighting, and other equity violations. - Clean and label real-world review data from platforms like Google, RateMDs, Vitals, Healthgrades - Collaborate on special logic — translating NLP outputs into report cards - Explore open datasets on health equity, maternal mortality, and public complaints to train models - Evaluate models for sensitivity, specificity, fairness metrics, and false positives - Create explainability tools (e.g., SHAP, LIME) to make outputs auditable and transparent ## Desired Skills - Strong Python + NLP toolkit experience (Hugging Face Transformers, spaCy, NLTK, or similar) - Familiarity with zero-shot/few-shot classification and prompt engineering - Bonus: Interest or coursework in fairness, healthcare, or social impact - Bonus: Prior use of datasets like MIMIC-III, Bias in Bios, or HealthReviewCorpus. Drop us your Github. ## What You'll Gain - Work under guidance of MIT, Oxford, and Harvard-affiliated researchers - Build tools with real-world accountability and ethical design stakes - Mentorship in ethical tech, bias auditing, and public interest product design We see thousands of applicants and there are patterns we can see with AI responses. Those candidates that are original impresss us the most. ## About the Company FairwAI is building for a world where systems treat people fairly — we're equally committed to building a team that reflects that world. Black, Indigenous, disabled, queer, and first-gen students are strongly encouraged to apply. ## About the Team ### Shaurjya Mandal – Head of Research, AI Systems & Clinical Innovation **Role:** Shaurjya leads FairwAI's research function and the development of its AI methodology — including structured retrieval architectures, sentiment and bias detection systems, and validation frameworks for fairness in clinical and high-stakes AI environments. He ensures FairwAI's research meets the standards of peer-reviewed clinical AI while remaining accessible and useful in real-world deployment. **Bio:** Shaurjya Mandal is a machine learning research scientist at Mass General Brigham and Harvard Medical School, where he develops and evaluates AI systems for clinical settings. His research sits at the intersection of responsible AI, healthcare equity, and applied machine learning — with published and applied work in algorithmic bias, fairness in clinical decision support, and AI safety for vulnerable populations. He holds an M.S. in Artificial Intelligence from Carnegie Mellon University, where he conducted research at the Robotics Institute on machine perception and learning systems. Prior to his work at Harvard, Shaurjya served as a research engineer at India's Defence Research and Development Organisation (DRDO) and contributed to AI policy and infrastructure projects across the MENA region, including the design of responsible AI deployment frameworks for healthcare and insurance systems in the United Arab Emirates. He is a Nucleate Pittsburgh fellow, a recognized convener in early-stage biotechnology and AI commercialization. At FairwAI, Shaurjya bridges frontier clinical AI research with practical, ethical deployment — ensuring that what we build for the most underserved populations is also held to the highest scientific standard. ### Dr. John Cooley – Technical Advisor **Role:** Leads FairwAI's technical architecture, AI compliance engine, and research partnerships. **Bio:** Dr. John Cooley is a renowned technologist and serial entrepreneur who holds five degrees from MIT: B.S. in Electrical Engineering, B.S. in Physics, M.S. in Electrical Engineering, an Engineer's Degree, and a Ph.D. in Electrical Engineering. He earned the David Adler Memorial Thesis Prize and the Morris Joseph Levin Award, recognizing his groundbreaking work in engineering and systems design. John was the CTO and later CEO of Nanoramic Laboratories, where he led the company to raise $100+ in capital and developed cutting-edge battery and nanotechnology solutions. With 15+ years of experience at the frontier of hardware-software integration and AI systems, John brings a rare blend of research rigor and venture-scale execution. He now advises FairwAI on tech architecture, compliance logic, and academic research integration across MIT and international institutions. ### Dr. Niousha Roshani – Social Systems Strategist **Role:** Co-leads FairwAI's strategy, focusing on culturally responsive AI, equity frameworks, and global engagement. **Bio:** Dr. Niousha Roshani is a leading voice in the intersection of AI, social justice, and public interest technology. She is a former Fellow at the Berkman Klein Center at Harvard University and co-founder of the Center for Democracy Development and Rule of Law at Stanford University. With a background spanning the UN system, Latin American human rights movements, and Stanford's impact tech community, Niousha brings a transnational lens to algorithmic fairness and ethical design. Her expertise ensures FairwAI builds tools that not only detect discriminat