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COMPANY OVERVIEW Pharos is an early-stage startup dedicated to improving patient safety in hospitals through advanced AI-powered reporting and analytics. Our mission is to make healthcare safer by automating hospital quality reporting and helping staff identify and prevent the root causes of avoidable harm. Our vision is an AI system reviewing every chart at scale, identifying patterns and giving clinicians the insights they need to prevent the 100k avoidable deaths that occur in U.S. hospitals every year. ABOUT THE ROLE This is a pivotal role as a founding member of the clinical AI research team at Pharos. As a Physician AI Researcher, you will bridge the critical gap between clinical expertise and AI development, ensuring our technology is both technically sophisticated and clinically sound. You will work in close partnership with the engineering team, bringing essential clinical perspective to every stage of product development. The scope of this role is intentionally broad - you will be an integral part of the founding team, working at the intersection of clinical medicine, AI research, and product development. You'll be defining clinical requirements, curating datasets, developing and evaluating AI models, validating outputs for clinical accuracy, and helping translate complex medical knowledge into systems that work in real-world hospital settings. Your work will directly contribute to Pharos's core mission: improving patient safety and ultimately saving lives by making healthcare safer. WHAT YOU'LL DO - Clinical-AI Bridge: Serve as the essential clinical voice in technical discussions, product decisions, and model development, ensuring clinical validity and real-world applicability of all our systems. - Model Development: Design, prototype, implement, and evaluate AI/ML models for healthcare quality reporting, patient safety monitoring, and clinical decision support. - Data Curation & Annotation: Define clinical data requirements, create annotation schemas, curate training datasets, and ensure data quality for model development. - Clinical Validation: Rigorously evaluate model outputs for clinical accuracy, safety, and utility. Identify edge cases, failure modes, and potential patient safety concerns. - Domain Expertise: Provide deep clinical knowledge about hospital workflows, quality metrics, safety events, medical terminology and clinical documentation. - Research & Literature: Stay current with clinical AI research, healthcare quality literature, and patient safety frameworks. Apply evidence-based approaches to our work. - Context Engineering & LLM Development: Design, test, and optimize prompts and workflows for large language models applied to clinical text and medical records. - Product Collaboration: Work closely with the product and engineering teams to translate clinical needs into technical requirements and user-facing features. - Hospital Engagement: Participate in conversations with hospital partners to understand their workflows, pain points, and requirements. - Documentation: Create clinical documentation, model cards, validation reports, and materials for regulatory submissions. WHAT WE'RE LOOKING FOR Required: - Medical Training: Medical degree (MD, MBBS, MBChB, MB BChir, or equivalent) with active or recent clinical practice experience. - Hospital Knowledge: Deep understanding of hospital workflows, quality processes, patient safety frameworks, and clinical operations. - Coding Proficiency: Strong programming skills in Python, including experience with data analysis libraries. - Analytical Thinking: Ability to approach problems systematically, think critically about data and models, and identify potential issues before they occur. - Communication: Excellent ability to communicate complex clinical and technical concepts to diverse audiences including clinicians, engineers, and business stakeholders. Strongly Preferred: - AI/ML Development: Hands-on ex