About Dyania Health

Dyania Health is a venture-backed company founded in 2019. Dyania's mission is to deploy cutting-edge and medically specialized AI that empowers clinicians to deliver optimal care, precisely when patients need it, by automating manual review of electronic medical records, the most time-consuming and inefficient process in modern healthcare. Dyania has developed Synapsis AI, an end-to-end large language model-based system built to understand and assess clinical characteristics in EMRs. Synapsis AI is designed for installation within the healthcare system's computing environment without removing any data from the healthcare system. Synapsis AI completes pre-screening on both unstructured and structured patient data, and deploys medical logic with temporal sensitivity to match dynamically changing patient characteristics with complex clinical trial criteria during the exact window of time that a given EMR may qualify for study protocol criteria.

As a vital member of our diverse team, our Clinical Research Associates (CRA) will collaborate closely with the AI Research and software engineering teams. Our CRA's also play a critical role in working with physicians at our client institutions to design and implement research protocols, publish results, and engage on implementation to ensure they are happy with the results Synapsis AI is giving them. Our clinical team has a 4-part focus:

(1) AI training strategy design, development of prompts and clinically relevant questions, and annotations of data as well as benchmarking to test and validate the performance of Synapsis AI regularly at scale.

(2) Scoping client partner needs to interpret, deconstruct and propose questions and focus areas. The goal is to transfer subjectivity in medicine to a "machine friendly" and objectively defined scope of projects

(3) Designing, exploring, and drafting protocols for retrospective observational research, evidence-guided care pathways, and real world insights and proceeding to implement projects and analyze results for research publications

(4) Ensure quality or results with sampling a review of what Synapsis AI is producing

Key Responsibilities:

• Development of medical cases utilized for training Dyania’s LLM
• Delineation of clinical logic for trial criteria matching
• Assessment of clinical trial protocols and composition of trial documentation
• Breakdown of inclusion and exclusion trial criteria into machine-friendly queries
• Evaluation and quality assurance of Synapsis AI performance to ensure clinical accuracy
• Design and draft of investigator initiated protocols for retrospective observational studies

Requirements

Required Qualifications:

• Medical Doctor (MD) or PharmD degree from an accredited US or EU university.
• Highly organized, strong attention to detail, and critical thinking.
• Comprehension of clinical guidelines to ensure accurate and up-to-date AI model training.
• Experience analyzing and drawing medical conclusions from clinical notes.
• Creative, solution-oriented, and flexible approach to problem solving.
• Proficiency in written/verbal communication in English.
• Strong communication skills for effective collaboration among interdisciplinary and multidisciplinary teams.

Preferred qualifications:

• Clinical trials design and clinical research procedures.
• Proficiency in Excel for data cleaning and transformations.
• Familiarity with AI/NLP, or SQL knowledge.
• Prior experience with EMR vendors in the US.

Team Culture:

• We lead with empathy for patients and our teammates
• We value small egos, self-awareness, and humility in our teammates
• We appreciate flexible and adaptive attitudes towards solving problems, as strategic priorities may shift
• We love diversity of thought, perspective, working style, skill set, knowledge, and interests amongst our team
• We value open dialogue and brainstorming across multidisciplinary teams

Dyania Health is an equal opportunity employer that is committed to workplace diversity and inclusion. We do not discriminate on the basis of race, gender, gender identity, color, religion, national origin, sexual orientation, or any other legally protected characteristic as outlined by federal, state, or local laws.