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Tenure-track faculty position at all levels in Data Science and Artificial Intelligence for Mec...
Tenure-track faculty position at all levels in Data Science and Artificial Intelligence for Mec...InsideHigherEd • Baltimore, Maryland, United States
Tenure-track faculty position at all levels in Data Science and Artificial Intelligence for Mec...

Tenure-track faculty position at all levels in Data Science and Artificial Intelligence for Mec...

InsideHigherEd • Baltimore, Maryland, United States
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General Description The Department of Mechanical Engineering at Johns Hopkins University invites applications for tenure-track or tenured faculty positions to lead the transformation of mechanical engineering through data science (DS) and artificial intelligence (AI). We seek scholars who advance the field through foundational contributions to DS and AI, as well as apply these methods to address grand challenges in mechanical engineering. We welcome candidates whose research pushes the boundaries of what is possible when deep expertise in DS / AI intersects with core mechanical engineering domains, including fluid dynamics, mechanics and materials, dynamics and controls, robotics, biomechanics and bioengineering in human health, energy systems, space engineering, planetary health, and climate resilience.

Examples of DS / AI-centric research thrusts of interest to Mechanical Engineering include, but are not limited to :

  • AI-accelerated modeling and simulation for multiphysics and multiscale problems
  • Physics-informed and hybrid learning for reduced-order and surrogate models
  • Uncertainty quantification, verification and validation, and risk-aware decision-making
  • Learning-enabled estimation, planning, and control for autonomous and human-in-the-loop systems
  • Digital twins and lifecycle analytics for complex engineered systems
  • Data-centric engineering, including sensing, data assimilation, experimental design, and streaming analytics
  • Generative and inverse design with autonomous design exploration
  • Edge and embedded AI for real-time inference and control
  • Foundations of trustworthy, robust, and interpretable AI for engineering decision-making
  • Agentic and Agent-based approaches
  • Computer vision
  • Natural Language Processing
  • DS / AI for resilience, sustainability, and planetary health

Johns Hopkins University has made a landmark investment in data science and artificial intelligence by establishing the Johns Hopkins Data Science and AI Institute (DSAI Institute). The Whiting School of Engineering at Johns Hopkins University is adding ~150 new faculty members over the next few years, constructing a new half-million-square-foot building to house the DSAI Institute, and deploying unparalleled computational infrastructure to support cutting-edge research and collaboration in this domain. This transformative initiative will establish Johns Hopkins University as one of the nation's largest and most distinguished engineering schools, featuring a world-leading AI research program. Faculty in the Department of Mechanical Engineering will play a vital role in this vision, with opportunities to engage across disciplines, access exceptional resources, and shape the future of data science and AI in engineering.

The Department of Mechanical Engineering at Johns Hopkins leads distinctive research programs. Its research spans core and emerging areas, including Mechanics and Materials, Robotics, Fluid Mechanics and Thermal Processes, Systems Modeling and Control, Mechanical Engineering in Biology and Medicine, Energy and the Environment, Micro / Nanoscale Science and Engineering, and Space Engineering. Its faculty thrives within a vibrant ecosystem of interdisciplinary collaboration that positions its faculty at the forefront of DS and AI innovation. The department operates the Johns Hopkins Turbulence Databases (JHTDB), a multi-terabyte open numerical laboratory that provides programmatic access to DNS datasets for data assimilation, model discovery, and ML benchmarking. Additionally, its faculty members are key contributors to the Artificial Intelligence for Materials Design Laboratory (AIMD-L). This automated high-throughput experimental facility generates rich microstructure-property datasets for AI-driven materials discovery and inverse design in extreme environments. Faculty also engage across an exceptional network of university institutes and centers that amplify DS and AI research impact including : the Laboratory for Computational Sensing and Robotics (LCSR) for learning-enabled perception, planning, and control; the Institute for NanoBioTechnology (INBT) for bioengineering research and discovery, the Hopkins Extreme Materials Institute (HEMI) for data-driven materials discovery and design; the Institute for Assured Autonomy (IAA) for trustworthy and verifiable autonomous systems; the Center for Environmental & Applied Fluid Mechanics (CEAFM) for physics-informed modeling of multiscale flow phenomena; the Mathematical Institute for Data Science (MINDS) for foundational theory underlying modern DS and AI methods; the Ralph O'Connor Sustainable Energy Institute (ROSEI) addressing clean energy challenges; the Malone Center for Engineering in Healthcare for medical innovation; the Johns Hopkins Institute for Planetary Health (JHIPH) at the nexus of environmental interventions and human health; and Space@Hopkins connecting civilian space research across the university. Faculty also collaborate with the Johns Hopkins Applied Physics Laboratory (APL), one of the nation's premier research and development organizations, which tackles grand challenges in national security, space exploration, and critical infrastructure. This interconnected ecosystem enables transformative research spanning from foundational algorithmic advances to high-impact applications across autonomous systems, extreme environments, sustainable energy, healthcare, space, and defense.

Qualifications PhD in Mechanical Engineering or a related field by the start date.

A record of research excellence and a clear vision for an independent, collaborative program in DS / AI for Mechanical Engineering.

Commitment to high-quality teaching, mentoring, and inclusive excellence.

Application Instructions Please submit in a single PDF or via the application portal :

Cover letter,

Curriculum vitae,

Two-page research statement,

Two-page teaching statement,

Three representative publications,

Names and contact information for at least three references.

Application portal : https : / / apply.interfolio.com / 175773

Review of applications begins : Applications received by December 14

th

, 2025, will be fully evaluated.

Start date : July 1, 2026, or as mutually agreed upon.

Rank : Open to all ranks; appointment and salary will be commensurate with experience.

To apply for this position, visit : apply.interfolio.com / 175773

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education / training and other factors, as reasonably determined by the University.

Total Rewards

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here : https : / / hr.jhu.edu / benefits-worklife / .

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.

Pre-Employment Information

If you are interested in applying for employment with The Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the HR Business Services Office at [email protected] . For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations or accessibility at Johns Hopkins University, please visit accessibility.jhu.edu .

Background Checks

The successful candidate(s) for this position will be subject to a pre-employment background check including education verification.

EEO is the Law :

https : / / www.eeoc.gov / sites / default / files / 2023-06 / 22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf

Diversity and Inclusion

The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion .

Vaccine Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. The COVID-19 vaccine does not apply to positions located in the State of Florida. We still require all faculty, staff, and students to receive the seasonal flu vaccine . Exceptions to the COVID and flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry. This change does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID-19 vaccination and provide proof of vaccination status. For additional information, applicants for SOM positions should visit https : / / www.hopkinsmedicine.org / coronavirus / covid-19-vaccine / and all other JHU applicants should visit https : / / covidinfo.jhu.edu / health-safety / covid-vaccination-information / .

The following additional provisions may apply, depending upon campus. Your recruiter will advise accordingly. The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.

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