Department of Biostatistics

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 Research Fellow in Biostatistical and Causal Machine Learning Methods – Dr. Nima Hejazi
Postdoctoral Research Fellowship in Biostatistics – Dr. Rui Wang, Dr. Michael Hughes
Postdoctoral Research Fellow for Statistical Methods in Population Health Disparities – Dr. Briana Stephenson
Postdoctoral Fellow – Dr. John Quackenbush
Postdoctoral Research Position in Biostatistics and Data Science – Dr. Rui Duan
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

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

Postdoctoral Research Fellow in Biostatistical and Causal Machine Learning Methods

Description:

A postdoctoral research fellowship position is available in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. The scientific goals of this position are the development, implementation, and evaluation of biostatistical methods for causal inference and machine learning, primarily as applied in the study of infectious diseases, including COVID-19 and HIV/AIDS. The successful postdoctoral candidate will be primarily supervised by and work closely with Dr. Nima Hejazi—with opportunities for co-supervision and co-mentorship from Drs. Sebastien Haneuse, Michael Hughes, and Xihong Lin—as well as collaborators at the Massachusetts General Hospital Biostatistics Center and the Fred Hutchinson Cancer Center. The scope of work will focus on non- and semi-parametric inferential statistical methods for applications related to COVID-19 (including its post-acute sequelae–“long COVID”), HIV/AIDS, and other high-impact infectious diseases. Specific research areas include the detection of effect modification and subgroup profiling using clinical histories, causal inference for effects of time-varying interventions in observational studies, and causal mediation analysis as applied to studies evaluating the efficacy of candidate preventive/therapeutic agents. The postdoctoral fellow will have opportunities for both methodological research and close collaboration with subject matter experts.

BASIC QUALIFICATIONS
Doctoral degree in Biostatistics, Statistics, Computer Science, Epidemiology, or a related quantitative field and with expertise in advanced statistical theory, causal inference and/or machine learning. Strong programming skills (e.g., R, C++, Python, Julia) are required and prior experience with infectious disease applications is a plus. Excellent written and verbal communication skills, and ability to work collaboratively and independently, are expected.

To apply, visit https://academicpositions.harvard.edu/postings/12724 .

Research Associate/Research Scientist

Description:

OVERALL RESPONSIBILITY
The successful candidate will work with Drs. Curtis Huttenhower and Wendy Garrett on overall scientific coordination for the Harvard Chan Microbiome in Public Health Center (http://hcmph.sph.harvard.edu). This individual will be responsible for high-level scientific planning, reporting, outreach, and mentoring for the project, working with both computational and experimental scientists in multiple labs that are part of the Center. There will be ample opportunities to plan new projects; prepare presentations, proposals, and manuscripts with the Center and affiliated PIs, students, and postdoctoral fellows; funding reporting; and coordinate with the broader HCMPH community.
PRINCIPAL DUTIES AND RESPONSIBILITIES (*Essential Functions)
·   * Deep technical expertise appropriate for project planning, execution, and mentoring in either or both of microbial genetics / molecular biology, or microbial genomics / computational biology. Either mostly-experimental or mostly-computational experience is appropriate, as long as the candidate has some familiarity with the other field.
·   * Regular mentoring of Ph.D. and postdoctoral scientists carrying out microbiome research, which includes bioinformatic screening for microbiome-derived bioactives, microbial and mammalian cellular growth and phenotyping assays, and gnotobiotic mouse screens with Dr. Wendy Garrett and the Harvard Chan Gnotobiotic Facility.
·   * Scientific text preparation, particularly manuscripts with Ph.D./postdoctoral trainees and project reports with Dr. Huttenhower.
·   Development of new HCMPH, and project-specific research goals and methods, and identification of new scientific opportunities and research directions for further exploration.
·   Manages scientific staff and trainees; responsibilities include: hiring, mentoring, career development, and assisting with performance reviews.
·   Regularly interacts with internal and external contacts, including Harvard and Broad scientists, engineers and postdocs, and external clinicians and industry leaders.
·   Oversees data generation and data analysis across various internal and external collaborators for the HCMPH.
·   Collaboration with microbiome-related study and technology platforms at the Harvard Chan School and Broad Institute.
·   Scientific communication, particularly advocacy for the HCMPH and national and international conference and symposium presentations detailing Center research.
·   Outreach to current and potential industry and foundation partners for project and bioactive lead development, including interactions with the Harvard Office of Technology & Development, the Harvard Chan Office of Research Strategy and Development, and the Harvard Chan Office of External Relations.
MINIMUM QUALIFICATIONS
·         Ph.D. in Molecular Biology, Computational Biology, or related fields, with advanced research skills and at least 5 years of related experience. Combination ofmolecular biology and computational expertise preferred.
·         Experience participating in and/or coordinating collaborative experimental or computational microbiology projects.
·         Excellent record of contributions, publications, presentations and scientific leadership responsibilities; primary or key author on major reports, presentations and papers.
·         Must have the ability to interact with and influence both internal and external interdisciplinary scientists, engineers, and clinicians.
·         Must be able to handle a variety of tasks, to effectively solve problems with numerous and complex variables, and to shift priorities rapidly.
·         Must have excellent staff oversight and mentoring skills.
·         Demonstrated success in working on complex, novel research problems.
·         Creativity, curiosity, and the desire, persistence and ability to create scientific advances in human microbiome science.
Title to be determined based on experience and committee review.

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

Description:

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.

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/11790

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 for Statistical Methods in EHR-Based Studies

Description:

This is a postdoctoral position with the scientific goals being the development, implementation, and evaluation of statistical methods for causal inference based on electronic health records (EHR) data. The postdoctoral fellow will work with Drs. Haneuse, Mukherjee, and Wang in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health, as well as their collaborators at Kaiser Permanente. The focus of the work will be on semi-parametric methods for handling missing data in EHR-based settings but may extend beyond, and will involve hands-on analysis of long-term outcomes following bariatric surgery.

Basic Qualifications

Doctoral degree in Biostatistics, Statistics, Computer Science, or a related field. Strong theoretical and programming skills (e.g., R, C++, Python, Julia) are required and experience with EHR data is a plus.

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/11008

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 Research Position in Biostatistics and Data Science

Description:

The Department of Biostatistics at Harvard TH Chan School of Public Health invites applications for a postdoctoral research fellow position focused on developing innovative statistical and machine-learning methods for analyzing and integrating various types of complex biomedical data (e.g., electronic health record data, claims data, biobanks). Areas of particular interest include (but not limited to): (1) genetic risk prediction for underrepresented populations; (2) distributed causal inference in clinical research networks; (3) statistical methods for high-dimensional data. The postdoctoral fellow will be supervised by Dr. Rui Duan at Harvard and will work closely with collaborators across multiple institutions. The appointment will be for a one-year contract with potential for renewal. The fellow will be expected to participate in methodological research leading to publications in top statistical and applied journals.

Basic Qualifications

1. Doctoral degree in Biostatistics, Statistics, Computer Science, or a related quantitative field.

2. Strong theoretical training in statistics or strong programing skills (R, Python, or C++) are desired.

3. Excellent communication skills and good track record of writing scientific papers.

Special Instructions:

Please submit:

  • a cover letter
  • a curriculum vitae
  • one-page research statement
  • one first author publication
  • three references

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/11807

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 Research Fellow for Statistical Methods in Population Health Disparities

Description:

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

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/10252

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 Research Fellow/Research Associate Position in Biostatistics and Biomedical Informatics

Description:

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.

Basic Qualifications:

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.

For the Research Associate position two years of postdoctoral experience is preferred.

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/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.