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 ([email protected]).