Institute for Clinical Research and Health Policy Studies

Center for Quantitative Methods and Data Science

The Center for Quantitative Methods and Data Science (QM&DS) is a new joint center of the Institute for Clinical Research and Health Policy Studies (ICRHPS), Tufts Clinical and Translational Science Institute, and Tufts University Data Intensive Studies Center (DISC) for computational scientists who are interested in the analysis of complex and multiscale biomedical data. Efficient and reproducible analyses of complex (multi-scale) biomedical data requires a synergy between statisticians, epidemiologists, computer scientists, bioinformaticians who bring complementary expertise to multidisciplinary collaborations. The center will provide an intellectual environment for computational scientists with different expertise to foster collaborations, develop new multidisciplinary training, generate independent research projects and also provide support to research collaborations. By concentrating on a variety of competencies, the center may become a referent contact for biomedical investigators who lead multidisciplinary research projects with many different components (e.g. cohort studies with multi-omics data).

The Center for Quantitative Methods and Data Science (QM&DS), in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center at Tufts CTSI and the Data-Intensive Studies Center (DISC) at Tufts University, invites you to attend several upcoming seminars. Registration for the seminars is free, but required. You will need to create a free I Learn account in order to register for the seminars. The zoom information will be sent to registered participants before the event. Please contact Anastasia Gurinovich ( to be added to the email list.

March 23, 2022, 2-3 PM: How useful is intervention response standard deviation?: Kathryn Barger, PhD

March 30, 2022, 2-3 PM: Computational Cognitive Models of Behavior Change in the Real World and at Scale: Peter Pirolli, PhD
Please register here >

April 6, 2022, 2-3 PM: Pathway-Based Methods to Characterize the Response to SARS-CoV2 in a Single Nucleus and Spatial Transcriptomic Atlas of the Liver: Yered Pita-Juarez, PhD

March 2, 2022: N-of-1 and Aggregated N-of-1 Trials: Motivation, Applications and Future Directions: Nicholas Schork, PhD
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January 26, 2022: Methods to Handle Mixtures of (Environmental) Exposures in Health Analyses: Laura Corlin
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December 15, 2021: Using Machine Learning to Increase Equality in Healthcare and Public Health: Emma Pierson
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December 1, 2021: NIH Funding Opportunities for Methodological Research in Mental Health: Christine Ulbricht

November 17, 2021: Tools, Methods and Community Actions for Reproducible Neuroscience: Jean-Baptiste Poline
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October 27, 2021: Nuts and Bolts of Meta-Analysis: Ludovic Trinquart
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September 29, 2021: I Thought I Knew What Randomization Was: Procedures and Inference by Ludovic Trinquart
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September 23, 2021: A Conversation with the New York Times
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June 16, 2021: Scalable Bayesian Flexible Joint Time Series Modeling: Michael Wojnowicz

June 9, 2021: What is the long-term effect of direct antiviral agents for Hepatitis C? A causal inference approach using ‘big data’: Sara Lodi

March 31, 2021: To Everything There Is a Season: Synchronization of Infectious Outbreaks: Elena Naumova
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February 17, 2021: Spatial epidemiological analysis and modeling of opioid decedent data: Thomas Stopka
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January 20, 2021: Single Cell Sequencing: Tanya Karagiannis

December 16, 2020: Reproducible Research: Karl Broman
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October 21, 2020: Vaccine Development: Norma Terrin

The Center for Quantitative Methods and Data Science, Tufts Clinical and Translational Science Institute, and Tufts University Data Intensive Studies Center are pleased to announce that the Training in Biomedical Data Science seminar series is now available for viewing on I Learn. Please enroll here to view recordings of each session. Creating a free account is required to view the sessions.

June 23: Study Design for Biomedical Data Science: Janis Breeze and Angie Rodday

June 30: Introduction to Sequence-Based Transcriptomic Analysis: Eric Reed and Albert Tai

July 14: Bioinformatics Analysis of Bulk RNA Sequencing Data: Rebecca Batorsky and Albert Tai

July 21: Bioinformatics Analysis of Single-Cell RNA Sequencing Data: Tanya Karagiannis and Eric Reed

July 28: Functional and Enrichment Analysis Methods for RNAseq Data: Rebecca Batorsky, Eric Reed, and Albert Tai

The Center for Quantitative Methods and Data Science at the Institute for Clinical Research and Health Policy Studies (ICRHPS) at Tufts Medical Center seeks faculty biostatisticians to provide methodological leadership for innovative biomedical research and teaching. Our institute provides a supportive academic environment for original methodological research and ample opportunities for collaborations. Tufts biostatisticians have a track record of success and have been integral to high-impact methodological advances, including predictive models used worldwide to predict health outcomes for patients with myocardial infarction and kidney disease, innovations in meta-analytic techniques and clinical trial design, evaluation of the heterogeneity of treatment effects, and development of machine learning methods for analyses of genetic and genomic data.

Faculty biostatisticians work closely with the Biostatistics, Epidemiology, and Research Design (BERD) Center at the Tufts Clinical and Translational Science Institute (CTSI), and collaborate with clinical, health services, and basic science researchers throughout Tufts University, Tufts Medical Center and affiliated institutions, and the Data Intensive Studies Center. In addition, they teach and mentor MS and PhD students in the Tufts Clinical and Translational Science Graduate Program. Faculty are eligible for Tufts University faculty appointments in the Medical School at appropriate level. 

Ideal candidates hold a PhD in Biostatistics or related field, have a track record of academic productivity, and some graduate-level classroom teaching experience. Demonstrated potential for securing external funding is also desirable. The new faculty will join a growing group of biostatisticians and data scientists, and have opportunities for developing their own research program in addition to providing statistical leadership to multidisciplinary research teams in biomedical and clinical sciences.   

Applicants should send a cover letter that includes a statement of current and future research interests, a curriculum vitae, and contacts of four references to:

Paola Sebastiani, PhD
Director of the Center for Quantitative Methods and Data Science
Director of the Biostatistics, Epidemiology and Research Design
Faculty of the Data Intensive Study Center. 

Consideration of applications will begin after January 15, 2021.  

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy and pregnancy-related conditions, disability status, protected veteran status, or any other characteristic protected by law. Women and minority candidates are particularly encouraged to apply.

Staff in the QM&DS center conduct research in biostatistics, epidemiology, computational biology, machine learning, and data science. The common link is the focus on biomedical data and the desire to combine different approaches to unveil biological processes that lead to disease, to build better prognostic and diagnostic models, and to contribute to improving public health.

Paola Sebastiani, PhD
Director, Center for Quantitative Methods and Data Science 

Norma Terrin, PhD
Scientific Director

Ludovic Trinquart, PhD
Director, Center for Clinical Trials

Anastasia Gurinovich, PhD

Tanya Karagiannis, PhD Student
Senior Statistician Associate

Benjamin Koethe, MPH

Jason Nelson, MPH

Angie Mae Rodday, PhD, MS
Assistant Professor 

Hocine Tighiouart, MS
Assistant Professor

Karin Knudson, PhD
Instructor and Data Scientist

Ye Chen, MS
Statistical Associate

Eric Reed, PhD
DISC Data Scientist

Rebecca Batorsky, PhD
Senior Bioinformatics Scientist

Andrew Williams, PhD
Assistant Professor

Albert Tai, PhD
Assistant Professor

Benjamin Sweigart
Statistician Associate

Laura Corlin, PhD
Assistant Professor

Tasneem Zaihra, PhD
Assistant Professor

Ellaina Reed
Research Project Coordinator

a. Pipeline for Genome Wide Association Studies
b. Coming Soon

Please check back for information on tutorials and courses.

Mailing Address:
Center for Quantitative Methods and Data Science (QM&DS)
The Institute for Clinical Research and Health Policy Studies
Tufts Medical Center
800 Washington Street, Box #63
Boston, MA. 02111

Physical Location:
35 Kneeland Street, 9th floor
Boston, MA 02111

Phone: 617-636-8819