Johns Hopkins, founded in 1876, is America's first research university and home to nine world-class academic divisions working together as one university.

Salary : $99,692 - $145,634

Johns Hopkins University: School of Education

Description

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.

About the Program

The Master of Science in Research and Evaluation Methods prepares students for rigorous research and evaluation work across educational, governmental, and non-governmental settings, with pathways in Qualitative Methods, Quantitative Methods, Program Evaluation, or an individualized plan of study. All students complete a shared foundation in social science research, statistics, and qualitative inquiry before specializing, and the program emphasizes methodological expertise, ethical and culturally responsive practice, and the ability to communicate findings to both academic and applied audiences.

The Quantitative Methods concentration equips students with advanced tools spanning machine learning, causal inference, survey design, data visualization, AI applications in evaluation, big data methodologies, distributed computing frameworks, and data scraping. The successful candidate will contribute to the program's methodological expertise in AI, machine learning, and NLP/LLM-based approaches, teaching within the Quantitative Methods concentration. Specifically, this Assistant Professor line will anchor and extend that concentration, bringing AI, machine learning, and NLP/LLM expertise to the curriculum while teaching within the shared foundation courses.

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 Required 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/

Application Instructions

Review of applications will begin October 17, 2026.

Applicants are required to provide:

• Curriculum Vitae
• A Research and Teaching Statement (in a single document) describing your interest and qualifications for the position, including information that describes relevant experiences (include evidence of effective teaching as available) and understanding of the School's mission, vision, and values.

Johns Hopkins, founded in 1876, is America's first research university and home to nine world-class academic divisions working together as one university.

Salary : $99,692 - $145,634

Johns Hopkins University: School of Education

Description

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.

About the Program

The Master of Science in Research and Evaluation Methods prepares students for rigorous research and evaluation work across educational, governmental, and non-governmental settings, with pathways in Qualitative Methods, Quantitative Methods, Program Evaluation, or an individualized plan of study. All students complete a shared foundation in social science research, statistics, and qualitative inquiry before specializing, and the program emphasizes methodological expertise, ethical and culturally responsive practice, and the ability to communicate findings to both academic and applied audiences.

The Quantitative Methods concentration equips students with advanced tools spanning machine learning, causal inference, survey design, data visualization, AI applications in evaluation, big data methodologies, distributed computing frameworks, and data scraping. The successful candidate will contribute to the program's methodological expertise in AI, machine learning, and NLP/LLM-based approaches, teaching within the Quantitative Methods concentration. Specifically, this Assistant Professor line will anchor and extend that concentration, bringing AI, machine learning, and NLP/LLM expertise to the curriculum while teaching within the shared foundation courses.

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 Required 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/

Application Instructions

Review of applications will begin October 17, 2026.

Applicants are required to provide:

• Curriculum Vitae
• A Research and Teaching Statement (in a single document) describing your interest and qualifications for the position, including information that describes relevant experiences (include evidence of effective teaching as available) and understanding of the School's mission, vision, and values.