Assistant Professor, Quantitative Research Methodologist (AI/ML/NLP)

Johns Hopkins University; Baltimore (MD); On-site; USD 100,000 - 146,000; Full time

Job summary

Johns Hopkins University School of Education invites applications for a full-time, tenure-track Assistant Professor position in quantitative research methodology with a focus on artificial intelligence, machine learning, and NLP. The role spans master's, EdD, and PhD programs and affiliated centers.

The ideal candidate will advance AI-informed courses, guide graduate students, and develop a rigorous research program in ML/NLP within education research contexts.

Qualifications

• PhD in education, psychology, sociology, statistics, policy, computer science, or related discipline.
• Demonstrated expertise in quantitative research methodology, including study design, measurement, and statistical inference.
• Applied experience with machine learning methods, including model development and evaluation.
• Experience with natural language processing and/or large language models in education or social science contexts.
• Evidence of, or trajectory toward, peer-reviewed scholarly publication.
• Proficiency in programming languages, including Python and R.

Responsibilities

• Teach graduate-level courses in quantitative research methods and AI/ML-related coursework across master's, EdD, and PhD programs.
• Advise and mentor graduate students, including doctoral students conducting AI/ML-informed research.
• Maintain an active research agenda involving machine learning, NLP, and/or LLM methods applied to substantive research questions.
• Lead school-wide efforts to ensure AI and computational methods are used transparently, accurately, and ethically.
• Contribute to the intellectual and methodological direction of AI and interdisciplinary initiatives.
• Collaborate with faculty across units and centers on interdisciplinary research and grant activity.
• Participate in curriculum development for quantitative methods and AI-related coursework.
• Engage in service to the department, school, and profession appropriate to rank.
• Foster connections with School of Education Research Centers.

Skills

Quantitative methods

Machine learning

NLP

Python

R

Statistical inference

Education research

Education

PhD in education, psychology, sociology, statistics, policy, or computer science

Tools

Python

R

Job description

About the Program

The Johns Hopkins University School of Education invites applications for a full-time, tenure-track Assistant Professor position in quantitative research methodology. A specialization in artificial intelligence, machine learning, and/or natural language processing is of particular interest. This position is central to the school's commitment to building interdisciplinary AI research capacity and will support quantitative methods training and AI-informed research in human development across the master's program, two doctoral programs, and affiliated research centers.

The ideal candidate will bring applied expertise in machine learning and large language model research methods to the program's quantitative training, contribute to the ongoing development of AI-informed courses within the concentration and across the school, and help prepare graduates to apply these methods rigorously in research and evaluation practice.

Responsibilities

• Teach graduate-level courses in quantitative research methods and AI/ML-related coursework across master's, EdD, and PhD programs
• Advise and mentor graduate students, including doctoral students conducting AI/ML-informed research
• Maintain an active research agenda involving machine learning, NLP, and/or LLM methods applied to substantive research questions
• Lead school-wide efforts to ensure artificial intelligence and computational methods are used transparently, accurately, and ethically in research
• Contribute to the intellectual and methodological direction of the school's AI and interdisciplinary initiatives
• Collaborate with faculty across units and centers on interdisciplinary research and grant activity
• Participate in curriculum development for quantitative methods and AI-related coursework
• Engage in service to the department, school, and profession appropriate to rank
• A connection with one or more of the School of Education's five Research Centers: https://education.jhu.edu/faculty-research/centers-institutes/

The expected base pay salary range for this position is $99,692 - $145,634.

Qualifications

• PhD in education, psychology, sociology, statistics, policy, computer science, or a related discipline
• Demonstrated expertise in quantitative research methodology, including study design, measurement, and statistical inference
• Applied experience with machine learning methods, including model development and evaluation
• Experience working with natural language processing and/or large language models in education or social science research context(s)
• Evidence of, or a clear trajectory toward, peer-reviewed scholarly publication
• Proficiency in statistical and/or programming languages, including Python and R
• Ability to teach graduate-level quantitative methods and/or AI-related coursework
• Significant experience conducting educational/social science research.

Preferred Qualifications

• Publication record involving AI/ML applications in education, social science, or a related applied domain
• Experience applying quantitative or AI/ML methods to questions in human development (e.g., developmental trajectories, longitudinal modeling, cognitive or socioemotional outcomes)
• Experience with LLM evaluation frameworks, including human evaluation protocols, rubric-based scoring, or LLM-as-judge approaches
• Experience securing or contributing to external grant funding
• Experience mentoring or advising graduate students, including at the doctoral level
• Familiarity with research ethics and IRB considerations specific to AI-involved research designs
• Prior classroom teaching experience at the graduate level
• Applied research or methodological experience across varied work settings (academic, government, industry, or nonprofit)
• Interdisciplinary collaboration experience across units such as education, computer science, or data science
• An interest in collaborations in support the university's Data Science/Artificial Intelligence (DSAI) Institute: https://engineering.jhu.edu/Datascience-AI/ECE/

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 characteristics. 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 or demographic characteristics that are irrelevant to the program involved.

Pre-Employment Information

If you are interested in applying for employment with 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 [e-mail]. For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations at Johns Hopkins University for disabilities, medical conditions (including medical conditions related to pregnancy or childbirth), accessibility, or religious reasons, please visit accessibility.jhu.edu.

Background Checks

After receiving a conditional offer, the successful candidate(s) for this position will be subject to a pre-employment background check including education verification. When deciding whether a candidate's conviction history is job-disqualifying, the University considers the nature and gravity of the offense, the time that has passed since the conviction, and the nature of the job being sought.

EEO is the Law

https://www.eeoc.gov/employees-job-applicants

Vaccine Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. 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. We still require all faculty, staff, and students to receive the seasonal flu vaccine.

Exceptions to the seasonal flu vaccine or COVID-19 vaccine (for SOM) requirement(s) may be provided to individuals with sincerely held religious beliefs or medical conditions that preclude them from receiving the vaccine. Requests for an exception must be submitted to the JHU vaccination registry. 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 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 candidates 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.