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 Fellow – Dr. John Quackenbush
Postdoctoral Research Fellow/Research Associate Position in Biostatistics and Biomedical Informatics – Dr. Tianxi Cai
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
Postdoctoral Research Fellow, Microbiome Analysis Core – Dr. Curtis Huttenhower

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

Postdoctoral Fellow, Microbiome Analysis Core

Description:

The Harvard T.H. Chan School of Public Health Microbiome Analysis Core is seeking a data analyst, either MSc or PhD level, for microbiome epidemiology and bioinformatics. The Microbiome Analysis Core, located in the Department of Biostatistics, supports a comprehensive computational and statistical platform for population studies of the human microbiome, its interaction with health and disease, and methods for data mining and machine learning in multi-omic data. This job will entail work with the Microbiome Analysis Core personnel applying and extending microbiome informatics and statistical methods, developed in the Huttenhower lab (e.g. MetaPhlAn, HUMAnN) as well as standards in the field (e.g. DADA2), to human microbiome profiles, including microbial communities assayed in disease, animal models, cross-sectional and prospective human cohorts, and associated clinical phenotypes and/or environmental/lifestyle exposure metadata. These studies generally have the goal of identifying features of the microbiome (16S amplicon, shotgun metagenomic, and shotgun metatranscriptomic sequencing, yielding taxa, gene families, enzymes, and/or pathways) associated with various phenotypes, exposures, and/or outcomes. There will be regular interactions with internal and external contacts, including scientists, collaborators, postdocs, students, and clinicians and industry leaders.

BASIC QUALIFICATIONS

MSc or Ph.D. degree in Biostatistics, Bioinformatics, Computer Science, Computational Biology, Molecular Biology, Biology/Life Sciences, or related fields.
Proficiency in R programming and Linux/Unix command line.
Preference given to candidates with experience in microbiome analysis, ordination and cluster analysis, sequence analysis, intermediate R programming, a background in biostatistics, and computing clusters (e.g. Slurm).
Excellence in research
Excellent oral and written communication skills
Ability to handle a variety of tasks, effectively solve problems with numerous and complex variables, and rapidly shift priorities.
Excellent attention to detail is required.

To apply, visit https://academicpositions.harvard.edu/postings/14372

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

Postdoctoral Fellow in Biostatistics

Description:

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.

BASIC QUALIFICATIONS

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

Description:

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.

BASIC QUALIFICATIONS

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

Description:

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.

BASIC QUALIFICATIONS

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

Description:

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

The application should include an indication of which preceptor or preceptors would be the candidate’s preferred choice. The list of preceptors can be found at
To apply, visit https://academicpositions.harvard.edu/postings/13910

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 of molecular 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.