Description
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 multi-modal data
derived from the clinical care processes at MSHS embedded in in a high-performance
computational infrastructure, world-class expertise in computer science, design and
engineering, faculty will be positioned to ultimately improve patient outcomes with AI
technology.
The Mount Sinai Health System (MSHS) is New York City's largest integrated delivery system
encompassing (with the addition of South Nassau Communities Hospital) eight hospital
campuses, a leading medical school, and a vast network of ambulatory practices throughout the
greater New York region. It was formed in 2013, when Mount Sinai combined with Continuum
Health Partners, with a vision to produce the safest care, the highest quality, the highest
satisfaction, the best access and the best value of any health system in the nation. The Health
System includes approximately 7,480 primary and specialty care physicians; 11 joint-venture
ambulatory surgery centers; more than 410 ambulatory practices throughout the five boroughs
of New York City, Westchester County, Long Island, and Florida; and 31 affiliated community
health centers.
Mount Sinai is a recognized leader in AI, ranked #1 on the new Nature AI index in 2024 as a
Leading Healthcare Institution.
https://clinicaldatascience.mountsinai.org/2024/10/01/mount-sinai-ranks-as-no-1-health-care
institution-according-to-nature-ai-index/
Founded in 1852, The Mount Sinai Hospital is one of the nation’s largest and most respected
hospitals, acclaimed internationally for excellence in clinical care. In 2023-24, The Mount Sinai
Hospital is on the U.S. News & World Report® “Best Hospitals” Honor Roll for the eighth straight
year. The Mount Sinai Hospital was ranked No. 1 in the nation in Geriatrics for the fourth straight
year and had nine other specialties in the top 22. Its total of 12 specialties ranked nationally in the
top 50 was one more than last year. These include a number 4 ranking in Cardiology and Heart
Surgery, 6th in Gastroenterology and GI Surgery, 9th in Neurology and Neurosurgery, 11th in both
OB/GYN and Orthopedics, 12thin both Cancer and in Pulmonology and Lung Surgery, 18th in both
Rehabilitation and in Urology, 21st in Diabetes and Endocrinology, and 36th in Ear, Nose and
Throat. It was also rated as “High Performing” in 20 out of 21 procedures and conditions. The
Mount Sinai Hospital consistently earns Magnet status for nursing care, and it is the only medical
center in New York State to earn Disease-Specific Care Comprehensive Stroke Center
Certification from The Joint Commission. The institution also received a Health Care Innovation
Award from the Centers for Medicare and Medicaid Services to open the first geriatric emergency
department in New York City, and its Mount Sinai Access service is one of the largest and most
sophisticated inpatient transfer services in the city.
IcahnSchool of Medicine at Mount Sinai
The Icahn School of Medicine at Mount Sinai: The Icahn School of Medicine at Mount Sinai
(ISMMS) was established in 1963 under a charter from the New York State Department of
Education. ISMMS was created as an academic partner to MSHS and together ISMMS and
MSHS comprised The Mount Sinai Medical Center (MSMC). It has earned distinction by multiple
indicators: No. 15 and No. 2 in the nation for National Institutes of Health funding overall and in
genetics, respectively, according to the Blue Ridge Institute for Medical Research, and among
the top 10 most innovative research institutions as ranked by the journal Nature in its 2017
Nature Innovation Index. (We note that, effective January 2023, ISMMS chose to withdraw from
the U.S. News and World Report rankings, putting into practice our leadership’s conviction of
their detrimental impact on medical education). These distinctions reflect a special level of
excellence in education, clinical practice, and research.
Windreich Department of AI and Human Health
We are the first Department of AI and Human Health focused on the development of safe AI
tools to improve human health. We have developed unique, world-class data and
computational resources to accelerate AI analysis. We are also committed to training the
next generation, with training in AI and human health. Within the department we are
expanding our internal and external partnerships to further enhance our AI efforts, not just
for the benefit of our own patients, but to make health care more accessible across the
world. Our mission is to ensure the safe, ethical, responsible, secure and effective use of
this technology in clinical care.
The Hasso Plattner Institute at Mount Sinai
The Hasso Plattner Institute for Digital Health at Mount Sinai (HPI.MS) within the Windreich
Department of Artificial Intelligence and Human Health is a research institute and
partnership funded by a generous gift from the Hasso Plattner Foundation. This
international academic initiative between the Icahn School of Medicine at Mount Sinai in
New York City and the Hasso Plattner Institute for Digital Engineering (HPI) in Potsdam,
Germany, combines an innovative healthcare system with world-class engineering
expertise. This offers unprecedented opportunities to implement HPI.MS’ mission of
shaping the future of digital health by developing advanced solutions that empower
patients and healthcare providers, ultimately improving global well-being and medical
discovery. The institute’s research leverages the latest technology to create novel
methodologies and bring together interdisciplinary expertise in the fields of machine
learning and artificial intelligence, multimodal data, health IT systems engineering, and
connected technology. In addition to its cutting-edge research initiatives, HPI.MS
encompasses a joint educational program to train the next generation of digital health
experts. Joint endeavors of HPIMS include AIRMS, a revolutionary unified data platform
equipped with the state-of-the-art computational frameworks and architectures, and
Digital Discovery Program, a comprehensive digital health research program of patient
centric health studies and clinical tools utilizing wearable, mobile and sensor
technologies.
The Hasso Plattner Institute at Potsdam
The Hasso Plattner Institute for Digital Engineering gGmbH is a non-profit institute
founded in 1998 and funded by the Hasso Plattner Foundation. It operates HPI in Potsdam
and, with the University of Potsdam, runs the privately funded Digital Engineering Faculty,
combining practice-oriented education with industry-connected research.
HPI’s Digital Health Cluster is an internationally connected center for digital health
research, education, and implementation. Through its Digital Health Partnership, it
advances high-impact research and real-world translation while training the next
generation of digital health leaders.
The HPI D-School strengthens this work through human-centered design, ensuring
solutions are user-focused and ethically grounded, while HPI Engine accelerates
commercialization and startup development. Together, they create a seamless pipeline
from research to real-world impact.
The Digital Health Partnership
The Digital Health Partnership is a multi-institution collaboration that brings together
scientific expertise in medicine and digital health, as well as technological expertise in data
management and health IT infrastructure to transform healthcare through innovation. By
advancing research, education, and real-world implementation, the partnership enhances
patient outcomes, optimizes patient journeys, strengthens disease prevention, and
accelerates clinical translation – shaping a future where technological progress directly
enhances health and wellbeing for all.
Flagship Institutional Resources
The Digital Health Partnership has established world-class strengths in artificial
intelligence, digital health, computer science, engineering, and data science. To ensure
that these innovations meaningfully and equitably improve clinical care and public health,
we aim to build a concentrated group of implementation science leaders in the Digital
Health Partnership whose work spans clinical, public health, behavioral, engineering,
machine learning, AI technology development, and AI governance domains. Recruits will
collaborate across HPI-MS and the Mount Sinai Health System, contributing to expanding
an internationally recognized program in applied AI. Read more about our flagship
programs and the available faculty opportunities.
High-Performance Computational and Data Ecosystem
The AI-Ready.Mount Sinai (AIR.MS) platform contains patient data generated from the
clinical care processes at the Mount Sinai Health System. AIRMS is a cloud-based, high
performance SAP HANA data platform with electronic health record (EHR) data in the
OMOP data format. It also contains metadata from and links to raw data sets in other
modalities, such as radiology, genomics and pathology. Researchers can access the data
through direct database access, AI agents, cohort query tools and the high-performance
computer. AIR-MS is integrated with Minerva, a high-performance computer with >21
petaflops of raw computational power and raw data sets, including radiology, genomics
and pathology. An expert team of 20+ PhD/MD computational scientists, biomedical
informaticists and computer scientists partner with researchers and clinicians to
effectively and efficiently utilize these resources for translational science.
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 to 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
Applicants should submit:
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 (Kelly.morgan@mssm.edu).
