Tenure-Track Faculty Positions in AI Implementation Science

Tenure-Track Faculty Positions in AI Implementation Science Windreich Department of AI & Human Health, Icahn School of Medicine at Mount Sinai New York City and the Hasso Plattner Institute (HPI) in Potsdam, Germany The Windreich Department of AI & Human Health (AIHH) at the Icahn School of Medicine at Mount Sinai, together with the Hasso Plattner Institute (HPI) in Potsdam, Germany, invites applications for four tenure‑track faculty positions as part of a new strategic concentration in implementation and translational science. Faculty will be core members of, and ambassadors for, the HPI‑Mount Sinai Digital Health Partnership (DHP), supported by the Hasso Plattner Foundation and Mount Sinai. We seek investigators at all ranks (Assistant, Associate, and Professor) whose research programs are interdisciplinary at the intersection of multiple science areas, including computer science, biomedical informatics, statistics, and implementation science, to accelerate the translation of safe and equitable AI algorithms and digital health innovations into real‑world clinical workflows within the Mount Sinai Health System. These faculty will expand the existing methodological foundation and collaborative infrastructure to advance clinical utility, cost‑effectiveness, sustainability, and policy relevance of AI innovations emerging from the Digital Health Partnership. Responsibilities Develop and lead an independent, extramurally funded research program in implementation science that leverages expertise and creates strong collaborations across the DHP, positioning the program to bridge the excellence of HPI in information system design and the world‑class clinical research enterprise of Mount Sinai. Spend a minimum of two weeks per Summer and Winter term on site at HPI in Potsdam, Germany, contributing to teaching in the HPI Master of Digital Health program and providing ongoing advising and supervision of master’s theses. Advance the translation, evaluation, and real‑world adoption of AI and digital health innovations using the AI‑Ready Mount Sinai (AIR.MS) platform. Mentor trainees engaged in implementation research, data science, public health, clinical research, and software engineering; provide mentorship to both HPI and Mount Sinai students participating in the Digital Health Partnership Academic Exchange Program. Engage in departmental, institutional, and collaborative service, including participation and leadership in Mount Sinai Health System implementation committees and development of innovative implementation efforts that synergize with independent research. 1. AI “Implementation in the Clinic” Scientist We are seeking a scientist at the intersection of AI, digital health, and clinical care to drive the design, implementation, and scale‑up of human‑centered technologies within a Learning Health System. Key Responsibilities Integrate AI and digital health tools into clinical workflows and EHR systems. Lead user experience and co‑design initiatives to ensure adoption and usability. Build scalable, provider‑centered implementation strategies using implementation science frameworks. Advance a Learning Health System model with continuous feedback loops and outcome evaluation. Collaborate with HPI Engine to accelerate translation from prototype to practice. Partner with the HPI Design Thinking School to cultivate interdisciplinary innovation capabilities. Ideal Candidate Expertise bridging computer science, engineering, implementation science, and healthcare delivery. Experience implementing AI tools in clinical settings. Deep understanding of EHR integration and clinical decision support. Demonstrated leadership in human‑centered design and translational innovation. 2. Implementation and Assurance Scientist This role supports ethical AI implementation strategies in the Mount Sinai Health system, ensuring safe, effective, and fair deployment of AI tools by addressing bias, accessibility, privacy, and trust. Key Responsibilities Design strategies for equitable deployment of AI systems. Identify and mitigate bias across demographic and clinical subgroups. Ensure accessibility and appropriate workflow integration. Safeguard privacy, data security, and patient trust. Establish monitoring frameworks for post‑deployment surveillance. Ideal Candidate Experience working within health system governance. Experience in development of real‑world performance monitoring. Knowledge of federal and New York State AI‑related policies. Knowledge of organizational psychology principles. Knowledge of qualitative and quantitative methods for evaluation of model trust and adoption. 3. Behavioral & Population Health Implementation Scientist This recruit focuses on applying AI to prevention, screening, chronic disease management, community health interventions, and patient‑centered outcomes research. Key Responsibilities Design and implement AI‑enabled interventions targeting prevention, screening, adherence, and chronic disease management. Build scalable models for deploying AI in safety‑net and resource‑constrained environments. Integrate behavioral science frameworks (e.g., COM‑B, behavioral economics, habit formation) into AI‑driven care pathways. Lead community‑engaged research and co‑design with patients, caregivers, and community‑based organizations. Develop and evaluate interventions that extend beyond clinical settings, such as remote monitoring and digital therapeutics. Evaluate impact across patient‑centered outcomes, engagement, equity, and long‑term health trajectories. Ideal Candidate Expertise in epidemiology, behavioral science, population health, or public health implementation. Experience designing and evaluating interventions that change patient or provider behavior. Strong background in community‑engaged research and/or health equity. Familiarity with digital health tools (mobile health, remote monitoring, patient engagement platforms). Experience working with diverse or underserved populations. 4. Implementation Methodologist & Clinical Trialist We seek an expert in hybrid effectiveness‑implementation trials, pragmatic trial designs, implementation evaluation frameworks, and economic analyses of digital health and AI implementations. Key Responsibilities Design and lead hybrid effectiveness–implementation trials (Types 1–3) for AI and digital health interventions. Develop pragmatic trial designs embedded within clinical workflows and health system operations. Apply causal inference methods to evaluate real‑world effectiveness using observational and quasi‑experimental data. Lead evaluation strategy across implementation outcomes (adoption, fidelity, sustainability) and clinical outcomes. Conduct economic evaluations, including cost‑effectiveness and budget impact analyses. Ideal Candidate Expertise in statistics, clinical trial design, epidemiology, and implementation science. Experience with pragmatic trials and/or embedded health system research. Strong background in causal inference and real‑world data analysis. Experience conducting economic evaluations of healthcare interventions. Track record of NIH or equivalent funding in methods or trials research. Ability to operate in complex health system environments and align research with operational priorities. Minimum Qualifications Doctoral degree (PhD, MD, MD/PhD, ScD, DrPH, or equivalent). Evidence of strong research productivity and, for senior ranks, a record of sustained extramural funding. Demonstrated excellence in implementation science, translational research, health equity, digital health evaluation, and/or AI translation. Demonstrated efficacy in teaching, mentorship, and contributing to an inclusive and supportive learning environment. Ability to work collaboratively and communicate effectively across disciplines, including clinicians, engineers, data scientists, computer scientists, and health system leaders. Application Instructions

1. A cover letter specifying the position(s) of interest.
2. Curriculum vitae.
3. Research statement (2 pages max).
4. Statement of teaching and mentoring philosophy (1 page max).
5. Contact information for at least three references.

Applications will be reviewed on a rolling basis, with priority given to submissions received by May 15th, 2026. For questions, please contact Kelly Morgan (View email address on click.appcast.io). #J-18808-Ljbffr Sarasota Memorial Hospital