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Tenure-Track Faculty Positions in AI Implementation Science Windreich Department of AI & Human Health, Icahn School of Medicine at Mount Sinai in 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, invite applications for four tenure-track faculty positions as part of a new strategic concentration in implementation and translational science. The 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 intersection of multiple science areas, including but not limited to computer science, computational science, biomedical informatics, mixed methods research designs, statistics, clinical trials, implementation and translational science. The overarching goal is to build on the existing DHP partnerships, platforms and processes to accelerate the translation of safe and equitable artificial intelligence algorithms, digital health innovations, and tools into real-world clinical workflows at the Mount Sinai Health System. This investment will establish a primary collaborative thrust for the DHP in implementation science, designed to bridge the gap between technical innovation and actionable, equitable health impact. 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 All faculty will: • Develop and lead an independent, extramurally funded research program in implementation science that leverages expertise and creates strong collaborations across the DHP. These research programs will be positioned to bring together the excellence of HPI in designing and engineering information systems with the world class clinical and biomedical research enterprise of the Mount Sinai Health System. • 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 (including course sessions) and provide ongoing advising and supervision of master’s theses. • Advance the translation, evaluation, and real-world adoption of AI and digital health innovations with research utilizing AI-Ready Mount Sinai (AIR.MS) as a foundational platform. • Mentor trainees engaged in implementation research, data science, public health, clinical research, and software engineering. Faculty members will be expected to participate in the Digital Health Partnership Academic Exchange Program by providing mentorship to both HPI and Mount Sinai students who are participating in the exchange. • Engage in departmental, institutional, and collaborative service. Faculty will be expected to participate in and lead implementation efforts in the Mount Sinai Health System. This includes an expectation to participate in the already existing implementation committees or programs, and to develop novel innovative implementation efforts that are synergistic with the faculty member’s independent research. We are conducting a coordinated recruitment for four complementary areas: 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. Role Overview: This role will lead the translation of AI-enabled research products into real-world clinical workflows, ensuring tools are usable, interoperable, and provider-centered. The successful candidate will champion co-design with clinicians and patients, apply design thinking methodologies, and embed AI seamlessly into EHR systems and clinical decision support environments. 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 This is a unique opportunity to shape the future of AI-enabled care by building durable innovation infrastructure and ensuring technology meaningfully improves provider experience and patient outcomes. 2. Implementation and Assurance Scientist This role is intended to support ethical AI implementation strategies in the Mount Sinai Health system. Ideal candidates will develop strategies to ensure safe, effective and fair implementation of AI tools, addressing bias, accessibility, privacy, and trust. Experience in partnering with communities, safety-net systems, or underserved populations is strongly valued. Potential areas of collaboration include AI governance, data engineering, and epidemiology. Role Overview: Mount Sinai maintains a dedicated AI Assurance Lab responsible for independent testing and validation of AI models before and after deployment. The Implementation and Assurance Scientist works closely with this lab to ensure that safe, effective, and fair deployment of AI models is paramount. The AI governance structure establishes policies and standards for the ethical and effective use of artificial intelligence throughout the Health System. The Assurance Lab conducts: • Technical validation and reproducibility testing • Evaluation of discrimination, calibration, and subgroup performance • Fairness and bias assessments • Stress testing under distributional shift and edge case scenarios • Ongoing post deployment performance monitoring This infrastructure ensures that AI systems meet defined institutional standards prior to clinical integration. To learn more about our AI governance structures, visit the Governance and Safety page of our AIHH Department website. Key Responsibilities: • Designing strategies for equitable deployment of AI systems • Identifying and mitigating bias across demographic and clinical subgroups • Ensuring accessibility and appropriate workflow integration • Safeguarding privacy, data security, and patient trust • Establishing 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 will focus on applying AI to prevention, screening, chronic disease management, community health interventions, and patient-centered outcomes research. Potential areas of collaboration include global public health, chronic and infectious diseases, and patient treatment processes. The recruit will further the strategic relationship between the Digital Health Partnership and the Institute for Health Equity Research. Role Overview We are seeking a Behavioral & Population Health Implementation Scientist to lead the design, deployment, and evaluation of AI-enabled interventions that improve prevention, screening, chronic disease management, and health outcomes across diverse patient populations. This role extends AI implementation beyond the clinic into real-world patient contexts, focusing on supporting behavior change, care access, and longitudinal outcomes. The successful candidate will integrate behavioral science, implementation science, and AI to drive scalable, equitable interventions across health system and community settings. This role is critical to ensuring that AI-driven innovation translates into measurable population health impact for the communities that we serve. 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 (e.g., remote monitoring, digital therapeutics, outreach strategies) • 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 (e.g., 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. Potential areas of collaboration include health system clinical trials, health economics, global public health, and policy. Role Overview We are seeking an Implementation Methodologist & Clinical Trialist to lead the design and execution of rigorous studies evaluating AI-enabled interventions using a range of clinical trial designs appropriate for healthcare settings. This role will anchor the Digital Health Partnership’s ability to generate high-quality evidence on effectiveness, implementation, and value. This evaluation can be based on hybrid trial designs, pragmatic methodologies, and advanced causal inference approaches. 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 (e.g., 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, 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 Why Mount Sinai & HPI? Faculty will join one of the world’s foremost academic medical centers for digital health and AI innovation within the Digital Health Partnership. With access to