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Job postings will be updated as they come in. Please check back regularly.

If you'd like to view other job boards and read some advice on how to apply for post-graduate research positions in psychology, see this helpful resource .

You should also check out PREDOC , or Pathways to Research and Doctoral Careers, a consortium site with job postings all over the country for recent graduates looking for pre-doctoral work!

Please note: These postings have not been approved or reviewed by the Department. They are unsolicited, and posted for your convenience.

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Doctor of Education Leadership

Additional Information

Download the Doctoral Viewbook
Admissions & Aid

America needs transformative leaders in preK–12 education whose passion for education quality and equity is matched by a knowledge of learning and development, the organizational management skills to translate visionary ideas into practical success, and a firm grasp of the role of context and politics in shaping leadership. Graduates of the three-year, multidisciplinary Doctor of Education Leadership (Ed.L.D.) Program at the Harvard Graduate School of Education will be prepared to become those leaders.

The Ed.L.D Program — taught by faculty from the Harvard Graduate School of Education, the Harvard Business School, and the Harvard Kennedy School — will train you for system-level leadership positions in school systems, state and federal departments of education, and national nonprofit organizations. Ed.L.D. is a full-time, three-year program built on a cohort learning model. Cohorts consist of up to 25 students from diverse professional backgrounds (including district/charter management leaders, nonprofit directors, principals, teachers, and policy researchers) who progress through the program together.

All Ed.L.D. students receive a full tuition funding package plus stipends, work opportunities, and a paid third-year residency at a partner organization.

The Ed.L.D. Program prepares graduates to do work for the public good in the American public education sector, whether that be at the system or state level. Specifically, the program is designed to accelerate the progress graduates make toward achieving meaningful impact in influential roles and/or crossing boundaries in the following spaces in the public education sector:

PreK–12 district or CMO leadership roles : superintendent of schools, chief academic officer, and/or deputy superintendent
Foundation/philanthropy roles: director, president and CEO, senior fellow
Education nonprofit roles : president or executive director of backbone or collective impact organizations which support preK–12 schools. Ed.L.D. graduates will lead education nonprofits that explicitly focus on improving outcomes and opportunities for children, families, and communities.
State or federal education leadership roles : commissioner or deputy commissioner roles. Could also include public education advocacy or education policy advisers to senior government officials.
Social Entrepreneurship and Innovation roles: Founder, CEO, president

Curriculum Information

The Ed.L.D. curriculum is a balance of multidisciplinary coursework and practice-based learning. Core courses and electives are taught by recognized leaders from across Harvard’s graduate programs in fields like data-based education reform, organizational change and innovation, and effective leadership strategies for urban schools. You will develop and test your leadership skills through team projects and an immersive third-year residency.

All students in the cohort take the same classes in four foundational content areas: learning and teaching, leadership and organizational change, politics and policy, adult development, and leadership inside and out (including one-on-one executive coaching). Courses taken during the first-year focus on practice-based learning and serve as the framework of your first-year experience.

Sample HGSE Courses

Leading Change
How People Learn
Ed.L.D. Proseminar
Leadership, Entrepreneurship, and Learning
Race, Equity, and Leadership
Practicing Leadership Inside and Out
Sector Change
The Workplace Lab for System-Level Leaders

View all courses in the Academic Catalog.

Each cohort member works with program advisers to choose an individualized sequence of electives from any of the Harvard graduate schools. You will work closely with the program faculty and staff during your second year to determine the best match with a partner organization for your third-year residency. Matches are driven by mutual interest between the resident and the partner organization, and each student's career and learning goals and geographic preferences.

Second Year Practicing Leadership Inside and Out
Driving Change
Education Sector Nonprofits
Negotiation Workshop
Coaching with Equity in Mind
Ethnic Studies and Education
Deeper Learning for All: Designing a 21st Century School System
Institutional Change in School Organizations, Systems, and Sectors

You will take part in a 10-month paid residency at one of our partner organizations. There, you will work on a strategic project which synthesizes your experience and learning into a written Capstone project. You will stay connected to your Ed.L.D. cohort and HGSE through technology and by returning to Harvard periodically for intensive workshops.

Paid Residency

Our partner organizations include school systems and departments of education, as well as some of the nation's most influential and dynamic nonprofit, mission-based for-profit, and philanthropic organizations.

You will be intentionally pushed out of your comfort zones and asked to work systemically and make a significant contribution to the partner organization. In addition, the residency will provide you with the professional mentoring, practical experiences, and network of connections they need to position themselves as future leaders in the education sector.

Strategic Project

You will define (with supervisors from your partner organization) a strategic project on which to focus. You will have the opportunity to lead one or two major efforts on behalf of the organization, such as the creation or implementation of current initiatives. The project allows you to practice and improve leadership skills, add important value to the mission and strategy of the partner organization, work systemically, and hold high-level accountability.

During the residency period, you will produce a written Capstone. The Capstone is a descriptive, analytic, and reflective account of your third-year leadership contributions to a strategic project within an Ed.L.D. partner organization. It is a demonstration of your ability to engage others, develop strategy to successfully address and diagnose challenges, work toward a vision and goals, and learn from the results.

Sample Topics

Accountability, Coherence, and Improvement: Leadership Reflection and Growth in the Los Angeles Unified School District
Leadership Development for Entrepreneurial Education Leaders Working to Build Public & Private Sector Support
Disrupting Teacher Preparation: Lessons in Collaboration and Innovation Across the Learning to Teach Community of Practice
Pursuing Educational Equality for English Language Learners

Sample Summaries

Breaking Down Silos in a School District: Findings from an Ed.L.D. Project in Montgomery County
Expanding Students' Access to Meaningful STEM Learning Opportunities Through Strategic Community Partnerships
Developing a New Teacher Leadership and Compensation System in Iowa: A Consensus-Based Process
Finding Great Teachers for Blended-Learning Schools

GSE Theses and Dissertations from Digital Access to Scholarship at Harvard (DASH)

Program Faculty

Ed.L.D. students learn with renowned faculty from the Harvard Graduate School of Education, Harvard Business School, and Harvard Kennedy School. Faculty from the three schools share their individual expertise in the Ed.L.D. Program and work collaboratively to provide a challenging and coherent experience for students. Faculty who teach in the Ed.L.D. core curriculum and advise Ed.L.D. students include:

Faculty Director

Frank D. Barnes

Frank Barnes is faculty director of the Doctor of Education Leadership Program. He has over 30 years experience as an educator, researcher, and organizer. As a chief accountability officer, he led turnaround efforts for large public school districts, including Boston Public Schools and Charlotte-Mecklenburg Schools.

Kathryn Parker Boudett

Ebony N. Bridwell-Mitchell

Jennifer Perry Cheatham

Elizabeth City

Candice Crawford-Zakian

Marshall Ganz

Adria D. Goodson

Deborah helsing.

Monica C. Higgins

Deborah Jewell-Sherman

Lisa Laskow Lahey

Mary Grassa O'Neill

Irvin Leon Scott

Catherine Snow

Michael L. Tushman

Martin west.

Applications Are Now Open

The deadline to apply is December 15, 2024.

Program Highlights

Explore examples of the Doctor of Education Leadership experience and the impact its community is making on the field:

Do We Need Happiness Teachers?

After a trip to meet with the Dalai Lama, an Ed.L.D. student says we do

Illustration of parents bringing children to school

Combatting Chronic Absenteeism with Family Engagement

As post-COVID absenteeism rates continue unabated, a look at how strong family-school engagement can help

Academic Position Openings

Applicants are welcome to apply for more than one position, but a separate application will be required for each position.

Open Job Opportunities – Quick Links Click on a link below to be taken directly to the application. All hyperlinked positions below are currently accepting applications.

Postdoc Jobs : Postdoctoral Fellow – Dr. John Quackenbush Postdoctoral Research Fellow/Research Associate Position in Biostatistics and Biomedical Informatics – Dr. Tianxi Cai Postdoctoral Research Position in Biostatistics – Drs. Francesca Dominici, Rachel Nethery, Danielle Braun Postdoctoral Research Position in Data Science – Dr. Francesca Dominici Postdoctoral Research Position in Quantitative Sciences for Cancer Research – Dr. Giovanni Parmigiani Postdoctoral Research Position in High-Dimensional Statistics/Computational Biology – Dr. Rong Ma Postdoctoral Fellow in Biostatistics – Dr. Jeff Miller Postdoctoral Research Position in Statistical Genetics and Genomics – Dr. Xihong Lin Postdoctoral Research Fellow in Artificial Intelligence – Dr. Junwei Lu

Research Associate/ Research Scientist Jobs : Research Associate/Research Scientist – Dr. Curtis Huttenhower

Postdoctoral Fellow in Biostatistics

Description:

The Junwei Lab at Harvard T.H. Chan School of Public Health led by Dr. Junwei Lu, invites applications for a Postdoctoral Research Fellowship. We are seeking candidates with strong backgrounds in statistics or artificial intelligence. The role of this position is to lead pioneering research in developing the methods and theory in the area of AI for science, especially for multi-omics data analysis in biomedical applications. This position will offer collaborations with interdisciplinary teams with experts both in AI, data science, and biomedical science with competitive salary, health insurance, and access to state-of-the-art research facilities on a vibrant campus.

BASIC QUALIFICATIONS

A PhD in (bio)statistics, computer science, applied mathematics, or related fields and demonstrated skill in quantitative research, big data analysis, and AI programming proficiency.

To apply, visit https://academicpositions.harvard.edu/postings/14265

This is a postdoctoral position developing statistical methods for finding patterns in complex biomedical data, working with Jeff Miller in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. Models and methods of interest include hierarchical regression models, latent factorization models, nonparametric Bayesian models, models for sequential data, mixture models, machine learning algorithms, and robustness to model misspecification. This postdoctoral position will involve working with Dr. Miller and collaborators to develop statistical methods and software tools for analyzing high-dimensional biomedical data from cancer genomics and clinical applications.

Doctoral degree in Statistics, Biostatistics, Computer Science, Applied Math, or a related field. Advanced expertise in Bayesian statistics and machine learning is essential. Strong programming skills are required (e.g., in Julia, Python, R, C++). Primary author on at least one publication in a leading peer-reviewed journal.

To apply, visit: https://academicpositions.harvard.edu/postings/14180

Postdoctoral Research Position in Statistical Genetics and Genomics

Postdoctoral Research Fellow position in statistical genetics and genomics is available at the Department of Biostatistics Harvard T. H. Chan School of Public Health. This position will be supervised by Dr. Xihong Lin (https://www.hsph.harvard.edu/lin-lab/), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods for analysis of large-scale whole genome genetic and genomic and phenotype data. Examples include large Whole Genome Sequencing association studies, biobanks, single-cell and CRISPR multiome data, integrative analysis of genetic and genomic data, causal mediation analysis and Mendelian Randomization, polygenic risk scores, and AI/transformer-powered analysis. We seek an individual with strong backgrounds in statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration with subject matter researchers and investigators in large NIH consortia.

Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, computational biology, strong research background in statistics and ML, programming, data analysis, strong genetic and genomic knowledge, as well as good written and oral communication skills.

To apply, visit: https://academicpositions.harvard.edu/postings/14227

Postdoctoral Research Position in High-Dimensional Statistics/Computational Biology

We are seeking a candidate with expertise in computational biology, machine learning, and/or high-dimensional statistics to work as a postdoctoral research fellow in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. Potential duties and responsibilities involve (i) identifying, formulating, and solving important theoretical or computational challenges arising from emerging single-cell technologies such as single-cell multiomics and spatial transcriptomics; (ii) analyzing single-cell omics data and software development; (iii) writing scientific articles and research proposals. The successful candidate will work with Dr. Rong Ma on computational or theoretical research projects surrounding integrative single-cell omics analysis, manifold learning, and high-dimensional statistics.

Ph.D. in applied math, biostatistics, computer sciences, computational biology, statistics, system biology, or related fields. Strong quantitative (computational or theoretical) research background. Knowledge of single-cell sequencing, differential geometry, or random matrix theory is encouraged but not required.

To apply visit: https://academicpositions.harvard.edu/postings/13972

Postdoctoral Research Position in Quantitative Sciences for Cancer Research

The Department of Biostatistics at the Harvard T.H Chan School of Public Health invites applications for a Postdoctoral fellow position funded in large part by an NIH training grant on Quantitative Sciences for Cancer Research. Candidates have latitude to choose among several mentors across various institutes at Harvard; research can range from the most applied to the most theoretical as long as there is a genuine commitment to its ultimate utility in cancer research.

The ideal candidate is an independent, solution-oriented thinker with a strong quantitative background and a clear commitment to cancer research. Other qualifications include: • Required: PhD in Statistics, Biostatistics, Computer Science, Data Science, or related field • Required: U.S. Citizenship or Permanent Residency • Preferred: Familiarity with multiple data science tools and ability to learn new tools as required. • Preferred: Excellent communication and writing skills.

This position is funded by an NIH T32 grant. Candidates must meet appointment eligibility criteria (career level and US citizenship or permanent residency), as outlined https://researchtraining.nih.gov/programs/training-grants/T32

Research Associate/Research Scientist

Application Procedures:

To apply for this position, submit your application through the Harvard ARIeS: Academic Recruiting Information eSystem at the following link:

https://academicpositions.harvard.edu/postings/11352

Additional Information: Harvard University seeks to find, develop, promote, and retain the world’s best scholars. Harvard is an Affirmative Action/Equal Opportunity Employer. Applications from women and minority candidates are strongly encouraged.

Postdoctoral Fellow

We are seeking a candidate with expertise in computational and systems biology to work as part of a multidisciplinary team developing methods relevant to the study of genetics, gene regulatory networks, and the use of quantitative imaging data as biomarkers. Our goal is to use these methods to better understand the development, progression, and response to therapy. The successful applicant will work directly with Dr. John Quackenbush, but will be part of a community of researchers consisting of Dr. Quackenbush, Dr. Kimberly Glass, Dr. John Platig, and Dr. Camila Lopes-Ramos, and members of their research teams.

Basic Qualifications

A PhD in computational biology, biostatistics, applied mathematics, physics, biology, or related fields and demonstrated skill in methods and software development and the analysis of biological data are required.

Additional Qualifications

The ability to work as part of a large, integrated research team and strong verbal and written communication skills are essential. Previous work in cancer biology/cancer genomic data analysis is welcome but not required.

https://academicpositions.harvard.edu/postings/11790

Postdoctoral Research Fellow for Statistical Methods in Population Health Disparities

The Department of Biostatistics at Harvard TH Chan School of Public Health invites applications for a Postdoctoral Research Fellowship focused on the development of statistical methods for population health disparities. The postdoctoral fellow will work with Dr. Briana Stephenson and collaborate with a multidisciplinary research team to develop innovative statistical and machine learning methods to address and identify bias and inequities in population health. Areas of interest include: identifying bias in healthcare access and delivery, statistical methods for high-dimensional exposures in minority populations, model-based clustering techniques for understudied populations, and survey sampling methodology for diverse population cohorts. Research applications will utilize data from cancer registries, national survey studies, and large prospective cohort studies. The postdoctoral fellow will develop their research and training agendas through formal mentorship, seminars, conferences, and an Individual Development Plan ( IDP ) to explore and identify the fellow’s professional needs and career objectives.

Basic Qualifications:

Doctoral degree in Biostatistics, Applied Statistics, Computer Science, data science or related field
Experience developing and implementing statistical methods
Experience analyzing healthcare or population cohort study data
Strong statistical programming skills (e.g. R, MATLAB , Python, C++, etc.)
Strong oral and written communication skills

Additional Qualifications:

Experience implementing Bayesian models
Experience processing and analyzing large datasets

Special Instructions:

• Cover letter • Curriculum vitae • One-page research statement and/or one representative first author publication • Two references

https://academicpositions.harvard.edu/postings/12614

Postdoctoral Research Fellow/Research Associate Position in Biostatistics and Biomedical Informatics

A Postdoctoral Research Fellow or Research Associate position in biostatistics and biomedical informatics is available at Harvard T.H. Chan School of Public Health. The positions involve developing and applying statistical and computational methods for analysis of electronic health records ( EHR ) data including narrative data extracted via natural language processing, codified phenotype data as well as large scale genomic measurements. We seek an individual with strong statistical and computing backgrounds and who has expertise in statistical and machine learning methods for big data. The work will involve development and application of statistical and informatics methods and algorithm for analyzing EHR data.

Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, strong quantitative research background, statistical and programming proficiency, as well as good written and oral communication skills.

https://academicpositions.harvard.edu/postings/10604

Additional Information:

Harvard University seeks to find, develop, promote, and retain the world’s best scholars. Harvard is an Affirmative Action/Equal Opportunity Employer. Applications from women and minority candidates are strongly encouraged.