Academic Position Openings

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

Assistant/Associate Professor of Biostatistics

Harvard T.H. Chan School of Public Health

The Department of Biostatistics at the Harvard T.H. Chan School of Public Health seeks candidates to fill a tenure-track faculty position at the assistant or associate professor level. We seek candidates with backgrounds in quantitative health science research in areas such as biostatistical theory and methods and/or machine learning, and data science, with demonstrated expertise in the development of new methods as well as a record of collaborative research. Candidates with a broad range of research interests are welcome and encouraged to apply; particular attention will be paid to applicants whose areas of interest include methodological work in any or all of clinical trials, infectious disease, or health disparities research . In addition to having a keen interest in the development and application of biostatistical methods and computation in health sciences, candidates should be enthusiastic about teaching, training, and mentorship through our graduate programs. Candidates should also be committed to fostering principles of diversity, inclusion, and belonging throughout their research and teaching activities.

Responsibilities will include methodological and collaborative research, and teaching and supervision of graduate students. Qualified applicants will have a doctoral degree in biostatistics, statistics, mathematics, computer science, computational biology, epidemiology, or a related field. Candidates are required to have their doctoral degree by the time the appointment begins, and academic rank will be determined in accordance with the successful candidate’s experience.

The Department of Biostatistics  offers an exceptional environment to pursue research and education in biostatistics while being at the forefront of efforts to benefit the health of populations worldwide. Our faculty are leaders in the development of methods for the design and analysis of clinical trials and observational studies, missing data, causal inference, precision health, network analysis, computational and systems biology, microbiome analysis, statistical genetics and genomics, neurostatistics, statistical and machine learning methods, and environmental statistics. Our innovative approaches to the analysis of massive health-related data are strengthened by a deep foundation in theory and application. The department prides itself on having strong mentoring and a supportive environment for assistant and associate professors. Our unique and diverse community provides unparalleled collaborative opportunities with academic departments across Harvard, the Dana-Farber Cancer Institute, and other world-class Harvard-affiliated hospitals.

Please apply to:  https://academicpositions.harvard.edu/postings/10448

For questions, please contact:

Chair, Search Committee for Assistant/Associate Professor of Biostatistics

c/o Susan Luvisi

Department of Biostatistics

Harvard T.H. Chan School of Public Health

Email: biostatjrsearch@hsph.harvard.edu

The Harvard T.H. Chan School of Public Health seeks to find, develop, promote, and retain the world’s best scholars.  We are committed to upholding the values of diversity, equity, and inclusion in our school and the communities we serve.

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

Information on resources for career development and work/life balance at Harvard T.H. Chan School of Public Health can be found at: http://hsph.me/resources-career-development-and-work-life-balance.

The committee will review applications on a rolling basis, beginning immediately, until November 15, 2021.

Other Academic Positions

Research Scientist

Description:

The Department of Biostatistics in the Harvard T. H. Chan School of Public Health has an immediate opening for a Research Scientist/Senior Research Scientist.  The candidate will play an active role in several projects in environmental statistics and epidemiology with a focus in the management, integration, methods development, and analysis of large and complex data sets.
This is an attractive position for someone that has interest in: 1) managing complex and large datasets of health claims data and environmental exposures that vary in time and space; 2) developing algorithms to link millions of individual-level health data longitudinally (e.g. Medicare Billing Claims); 3) developing methods (e.g. machine learning) to integrate datasets on health information with datasets on environmental exposures; and 4) developing and applying statistical methods (e.g. Bayesian statistics and causal inference) to analyze the data and interpret results.
The position will require active collaboration with teams of researchers. Our team of data scientists, statisticians and epidemiologists conducts research on a broad range of issues, including air pollution, and climate change (see https://www.hsph.harvard.edu/nsaph/ for more details on the group and research). The successful candidate will take an active role in the leadership of several ongoing projects. They will lead and manage the data pipelines, as well as instruct and mentor undergraduate, masters students, PhD students and postdoctoral fellows in the statistical analyses of spatio-temporal data and lead and contribute to grant proposals.

Basic Qualifications:

  • PhD in Biostatistics, Statistics or Computer Science or related field.
  • Experience in handling very large datasets.
  • Experience in processing and managing health claims data.
  • Knowledge of R, SAS, and Python.
  • Interest in open-source software, reproducibility and data management

Additional Qualifications:

  • Familiarity with multiple data science tools and ability to learn new tools as required.
  • Experience with version control systems, in particular Git and GitHub.

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/10606

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

Research Associate/Scientist

Description:

We are looking for a bioinformatician or computational biologist to work with data from a wide variety of experimental platforms, with a focus on high-throughput sequencing technologies. This role provides a unique opportunity to participate in exciting and rewarding world-class research that is making a profound impact on human health.
About us
The Harvard Chan Bioinformatics Core (HBC) is a center for bioinformatics research, services and training at the Harvard T.H. Chan School of Public Health. We work closely with biomedical scientists across Harvard to implement approaches for analysis, interpretation, visualization and distribution of scientific discoveries using omic information. HBC projects are a mix of short-and long-term collaborations. Our team includes scientists from different disciplines who work with biomedical research groups within the Harvard, MIT and Broad communities, as well as within industry. In addition to the collaborative projects, our core has an educational mission, and several members of the core also participate in training activities, with the goal to enable researchers to analyze their data independently. The HBC emphasizes teamwork and a supportive environment where we learn from each other.
About you
You have a background in biomedical or quantitative science and a strong interest in working with medical and/or biological researchers. You thrive on scientific challenges, and enjoy collaborating with an interdisciplinary team. You can combine your knowledge of biology and computation to excel at communicating with programmers and wet-lab scientists alike. You are an independent learner, are keen to learn and apply new methods, and are motivated to continually expand your skills. You follow best practices for code and data management, have good organization skills, and are capable of simultaneously working on different projects and deadlines. You are experienced with high-throughput sequencing analysis and are comfortable mentoring junior researchers. Optionally, you have experience and interest in teaching all of the above-mentioned skills.
Duties
The Bioinformatician will support selected research projects, working independently with researchers at the Harvard Chan School, Harvard and the broader Boston biomedical community. They will provide expertise in the use of specialized bioinformatic tools and analysis methods to researchers and collaborate in analyzing and interpreting their data.
Reporting to the HBC Director and Associate Director, and coordinating closely with other Core staff, the applicant will analyze incoming data using existing analytical approaches commonly used in the Core, and assess and/or develop new methods where appropriate. They will document their work thoroughly, and provide manuscript-level reporting of final analyses and results. The applicant will summarize, analyze and visualize data using advanced techniques, and provide direct links to related informatics analysis tools. Other duties will include data management (coordinating with collaborating Research Computing groups and Core developers to ensure consistent data storage), participation in Core and lab meetings and other collaborator meetings around various campuses and liaising with collaborating researchers. Where appropriate, the applicant may participate in developing manuscripts for publication.

The Department of Biostatistics in the Harvard T. H. Chan School of Public Health has an immediate opening for a Research Scientist/Senior Research Scientist.  The candidate will play an active role in several projects in environmental statistics and epidemiology with a focus in the management, integration, methods development, and analysis of large and complex data sets.

This is an attractive position for someone that has interest in: 1) managing complex and large datasets of health claims data and environmental exposures that vary in time and space; 2) developing algorithms to link millions of individual-level health data longitudinally (e.g. Medicare Billing Claims); 3) developing methods (e.g. machine learning) to integrate datasets on health information with datasets on environmental exposures; and 4) developing and applying statistical methods (e.g. Bayesian statistics and causal inference) to analyze the data and interpret results.
The position will require active collaboration with teams of researchers. Our team of data scientists, statisticians and epidemiologists conducts research on a broad range of issues, including air pollution, and climate change (see https://www.hsph.harvard.edu/nsaph/ for more details on the group and research). The successful candidate will take an active role in the leadership of several ongoing projects. They will lead and manage the data pipelines, as well as instruct and mentor undergraduate, masters students, PhD students and postdoctoral fellows in the statistical analyses of spatio-temporal data and lead and contribute to grant proposals.

Basic Qualifications:

  • Doctoral degree in biological sciences, statistics or related computational field (eg. computational biology or bioinformatics) required.
  • Scripting abilities (Python familiarity, R proficiency, shell scripting) required.
  • Working knowledge of biology, genetics and cell biology required.
  • Experience in at least one of the following next-generation sequencing domains required:
    • Whole genome or Exome-sequencing
    • Bulk RNA-seq
    • Small RNA-seq
    • Single cell RNA-seq
    • ChIP-seq / ATAC-seq
    • Bisulfite-seq
    • Nanopore/PacBio long read analysis
  • Demonstrable ability to interpret and analyze data sets and present results.

Additional Qualifications:

  • Knowledge of functional analysis (enrichment studies, GSEA, networks), data management and visualization.
  • Excellent written English and a familiarity with presenting biological results.
  • Strong interpersonal skills.
  • Statistical background experience.
  • Github or other version control experience
  • Ability to produce reproducible code (R Markdown, Latex, Jupyter notebooks, etc)

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/10457

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

Research Associate/Scientist

Description:

The Harvard Chan Microbiome in Public Health Center (HCMPH, https://hcmph.sph.harvard.edu), co-directed by Drs. Curtis Huttenhower and Wendy Garrett at the Harvard T.H. Chan School of Public Health, is seeking a senior scientist at the Research Associate, Research Scientist, or Senior Research Scientist level to direct the Harvard Chan Microbiome Analysis Core (HCMAC, https://hcmph.sph.harvard.edu/hcmac/). The HCMAC provides collaborative analysis activities for the human microbiome and other microbial communities in public health population studies, currently comprising over 70 funded projects at the Harvard Chan School, throughout the Boston life sciences community, nationally, and internationally.

The Research Associate/Scientist’s responsibility will be to manage these microbiome research collaborations with the HCMAC team, which comprises a group of full- and part-time bioinformatics and biostatistics analysts and software developers working in association with the Huttenhower lab. This includes grant and project preparation and management with current and potential collaborators, experimental design and analysis consulting, management of HCMAC personnel, and hands-on computational microbiome analysis when appropriate. HCMAC projects typically consist of population-scale microbiome studies including metagenomic and 16S rRNA gene sequencing, gut microbiome metabolomics and other multi-omics, human genetic associations, and environmental, exposure, demographic, and other medical covariates. Examples of recent projects include:

• Data portal for the BIOM-Mass Biobank for Microbiome Research in Massachusetts (https://biom-mass.org), a Harvard Chan initiative including, initially, stool microbiome sampling for 25,000 women from the Nurses’ Health Study II (PMID 33883746).
• Services through the Massachusetts General Hospital (MGH) Center for the Study of Inflammatory Bowel Disease, including the Human Microbiome Project Inflammatory Bowel Disease Multi-omics Database (http://ibdmdb.org).
• A variety of studies on the interaction of diet, the environment, and cardiometabolic health outcomes with the gut microbiome (e.g. PMIDs 34333506, 33926968, 34114015).
• Close collaboration with the Harvard Chan Microbiome Collection Core (https://hcmph.sph.harvard.edu/hcmcc/) to facilitate an additional 25 projects using direct-to-participant microbiome sampling kits for culture-based and molecular data generation.
• Broadly recommending microbiome scientific priorities and capabilities for local and global public health training and practice (PMID 33820996).

This advanced position will have leeway to direct and carry out research projects within HCMAC, taking advantage of (and extending) its existing bioinformatics infrastructure for automated microbiome sequence quality control, amplicon processing, taxonomic profiling, functional profiling, strain profiling, metatranscriptomics, multi-omics, and downstream statistics and visualizations. Strong interpersonal skills as well as some computational experience are required, as is the ability and willingness to collaborate with and coordinate among diverse groups throughout Boston and within the Harvard Chan School.

Basic Qualifications:

Doctoral degree in Bioinformatics, Computer Science, Biostatistics, Biology, or related field; experience with quantitative biological project management; strong, detail-oriented writing and communication skills; working knowledge of Linux/Unix software environments for scientific computing; familiarity with Python and/or R; excellence in research, communication, and collaboration skills, as evidenced by publication record; highly responsive, self-motivated, and proactive with the ability to juggle a variety of tasks, effectively solve problems with numerous and complex variables, and rapidly shift priorities; proven effective leadership and teamwork capabilities; in-depth knowledge of microbiome research / microbial community analysis.

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/10524

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

Postdoctoral Research Position in Biostatistics

Description:

The Department of Biostatistics at the Harvard T.H. Chan School of Public Health invites applications for a Postdoctoral Fellow position for statistical methods development to address questions of climate change and air pollution regulatory policy.  Expertise in causal inference and machine learning is desirable but not necessary. The Postdoctoral Fellow will work with a multi-disciplinary team with expertise in statistical methods, epidemiology, climate science, and biomedical science.   The position will be under the joint supervision of Dr. Francesca Dominici in the Department of Biostatistics and Dr. Rachel Nethery, and in collaboration with Dr. Danielle Braun. Applicants should have an interest in developing and applying novel and state-of-the-art statistical and data science methods in environmental health.
Qualifications:
Doctoral degree in Computer Science, Statistics, Biostatistics, or related field.
Experience in analyzing real data, strong programming skills, and familiarity with statistical methods is preferred.
Excellent communication and writing skills desired.
The ideal candidate is an independent, solution-oriented thinker with a strong background processing very large data sets, applying analytical rigor and statistical methods, and driving toward actionable insights and novel solutions.
Duties and Responsibilities
The Post-doctoral Fellow will contribute to the effort of:
·   Analyzing environmental health effects in big data
·   Collaborate with our biostatistics and data science group
·   Writing scientific articles and research proposals

Basic Qualifications:

  • PhD in Biostatistics, Statistics or Computer Science.
  • Experience in air pollution health studies (desired).
  • Experience in handling very large spatial datasets.
  • Experience in applied statistics and computational methods.
  • Knowledge of R, SAS, and Python.
  • Interest in open-source software, reproducibility and data management.

Additional Qualifications:

  • Familiarity with multiple data science tools and ability to learn new tools as required.
  • Experience with version control systems, in particular Git and GitHub.

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/10603

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

Postdoctoral Research 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.
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.
Duties and Responsibilities
The Post-doctoral Fellow will contribute to the effort of:
·   Analyzing environmental health effects in big data
·   Collaborate with our biostatistics and data science group
·   Writing scientific articles and research proposals

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/8437

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

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/10524

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

Postdoctoral Research Fellow Positions in (i) Network Science and (ii) Biomedical Smartphone Research

Description:
The Onnela Lab in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health is seeking candidates with a Ph.D. in biostatistics, applied mathematics, statistical physics, computer science, or a related quantitative field for two-year Postdoctoral Research Fellow positions. These positions involve developing statistical methods, data analytic tools, and mathematical models for analyzing two different types of systems. In the first area, statistical network science, we develop methods that are at the intersection of statistical learning and network science with applications in social and biological networks. In the second area, smartphone-based digital phenotyping, we develop tools and methods for analyzing data collected by our smartphone platform. Our ongoing applied studies in this area involve diverse patient populations from neurology to psychiatry and oncology. The candidates can focus on one of these areas only or may work across both, depending on interests and expertise.

Qualifications:
Doctoral degree in biostatistics, computer science, applied mathematics, statistical physics, or a related quantitative field. Excellent programming skills in Python or similar language, as well as strong oral communication and writing skills are 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/8588

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.

Information on resources for career development and work/life balance at SPH can be found at: Career development and work/life balance.

For more information about the lab, please visit https://www.hsph.harvard.edu/onnela-lab/.

Postdoctoral Research Position in Statistical Genetics and Genomics

Description:
Postdoctoral Research Fellow position in statistical genetics and genomics is available at Harvard T.H. Chan School of Public Health. This position involves developing and applying statistical and computational methods for analysis of high-throughput genetic and genomic data, including Whole Genome Sequencing association studies, integrative analysis of genetic and genomic data high-dimensional phenotype analysis, and genome-wide epigenetic association studies. We seek an individual with strong statistical, computing and genetic backgrounds and who has expertise in statistical and computational methods for big data, statistical genetics and genomics. The work will involve both methodological research with department faculty and collaboration with subject matter researchers.

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

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/8842

Additional Information:
Administrative questions regarding this position can be sent to Susan Luvisi at biostat_postdoc@hsph.harvard.edu.
Scientific questions regarding this position can be sent to Xihong Lin
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.
Information on resources for career development and work/life balance at SPH can be found at Career development and work/life balance.

Postdoctoral Research Position in Environmental Health and Biostatistics

The Department of Environmental Health together with the Biostatistics Department at the Harvard T.H. Chan School of Public Health invites applications for a Postdoctoral Fellow position for the analysis of large-scale environmental health data. The Postdoctoral Fellow will work with a multi-disciplinary team to investigate the impact of air pollution and other exposures on risk for and progression of Alzheimer’s disease and related dementias (AD/ADRD), and identify the complex interactions of individual-level, environmental and societal factors that lead to increased vulnerability in AD/ADRD.

The position will be under the supervision of Dr. Antonella Zanobetti in the Department of Environmental Health, and Drs. Francesca Dominici and Danielle Braun in the Biostatistics Department. Applicants should have an interest in applying novel and state-of-the-art statistical and data science methods in environmental health. The specific position involves: (1) analysis of short- and long-term effects of air pollution and temperature on hospital admissions for AD/ADRD in Big Data applications using two cohorts (Medicaid and Medicare enrollees in the continental US), (2) identification of vulnerable subpopulations, (3) exposure-response functions, (4) disentangle the effects of air pollution exposure from other multiple confounding factors (socio-economic (SES), neighborhood-level factors such as green space and noise), (5) development and application of statistical models, including causal inference methods.

Qualifications:

Doctoral degree in Biostatistics, Applied Statistics, Environmental Health, or related field.

Experience in analyzing real data, air pollution health studies, public health, strong programming skills, and strong statistical methods are preferred.

Excellent communication and writing skills desired.

The ideal candidate is an independent, solution-oriented thinker with a strong background in statistical methods and processing very large data sets, applying analytical rigor and driving toward actionable insights and novel solutions.

Duties and Responsibilities
The Post-doctoral Fellow will contribute to the effort of:

  • Data integration from different data sources
  • Analyzing environmental health effects in big data
  • Refine and improve statistical methods to disentangle the effects of air pollution exposure from other confounding factors by leveraging approaches for causal inference and correct for potential outcome misclassification and exposure error
  • Apply machine learning methods to identify co-occurrence of individual-level, environmental, and societal factors that lead to increased vulnerability
  • Collaborate with our biostatistics and data science group
  • Writing scientific articles and research proposals
  • Participate in weekly meetings with supervisors, reporting on work performed and suggesting additional analysis or modifications in current procedures
  • Oversee the activities and mentor other research staff / students.

 Basic Qualifications

  • PhD in Biostatistics, Applied Statistics, Environmental Health.
  • Experience in air pollution health studies.
  • Experience in handling very large spatial datasets.
  • Experience in applied statistics and computational methods.
  • Knowledge of R, SAS, and Python.
  • Interest in open-source software, reproducibility and data management.

Additional Qualifications

  • Familiarity with multiple data science tools and ability to learn new tools as required.
  • Experience with version control systems, in particular Git and GitHub.

To apply

Please submit to Antonella Zanobetti at azanobet@hsph.harvard.edu.

  • a cover letter
  • a curriculum vitae
  • 1 page research statement
  • at least three names for references