Postdoctoral Research Fellow

Harvard University

United States

December 25, 2021

Description

Position Title Postdoctoral Research Fellow

School Harvard T.H. Chan School of Public Health Department/Area Nutrition Position Description

The Departments of Nutrition and Biostatistics at the Harvard T.H. Chan School of Public Health invite applications for a Postdoctoral Fellow for statistical methods development and application to examine the human health impacts of environmental change in Madagascar. Expertise in causal inference and machine learning is desirable but not necessary. The position will work with a multi- disciplinary team with expertise in statistical methods, ecology, epidemiology, climate science, and planetary health. The position will be under the joint supervision of Dr. Christopher Golden in the Department of Nutrition and Dr. Francesca Dominici in the Department of Biostatistics. Applicants should have an interest in developing and applying novel and state- of-the-art statistical and data science methods in planetary health. This research fellowship will last for at least 2 years pending successful performance in the first year. The post-doc will be based in Boston, where we have a rich community of researchers investigating the interrelationship of ecosystem transformation and human health.

Search: We are looking to hire a researcher with a strong data science and/or epidemiological background to 1) integrate climate (e.g., temperature, rainfall, soil moisture), environmental (e.g., forest cover, agricultural production, land use change), and health (e.g., monthly incidence data for 23 conditions from more than 3,000 clinics) data; and 2) analyze exposure pathways that connect climate and environmental data to health outcomes.

Duties and Responsibilities The position will contribute to the effort of:

· Collaborate with a data engineer to integrate the aforementioned data streams into an interoperable research data platform

· Liaise between the Ministry of Health in Madagascar and the HSPH research team to develop research question priorities

· Use cutting-edge statistical methods for big data to analyze the human health impacts of environmental change

· Write up research reports for the Ministry and for peer-reviewed publication

· Collaborate with our biostatistics and data science group

Basic Qualifications

· Doctoral degree in Computer Science, Statistics, Biostatistics, or related field.

· Experience analyzing real data with strong programming skills

· Excellent communication and writing skills.

· Experience in handling very large spatial datasets.

· Experience in applied statistics and computational methods.

· Knowledge of R, SAS, and Python.

· Skills in remote sensing data applications strongly preferred

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.
  • Interest in open-source software, reproducibility and data management.
  • 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.
  • · Preference for strong skills in data visualization for figures and/or web tools

    Special Instructions

    To apply: Please submit a CV and brief cover letter detailing relevant experience and reason for interest in the project to Dr. Chris Golden (golden@hsph.harvard.edu). Please also send the names of three references. Applications are due by December 20th though may be considered thereafter. Interviewing will take place in late January. Position will start between April and September 2022.

    Contact Information

    Dr. Christopher Golden, Assistant Professor of Nutrition and Planetary Health

    Contact Email golden@hsph.harvard.edu Equal Opportunity Employer

    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.

    Minimum Number of References Required 3 Maximum Number of References Allowed 5

    Supplemental Questions

    Required fields are indicated with an asterisk ().

    Applicant Documents

    Required Documents

  • Curriculum Vitae
  • Cover Letter
  • Statement of Research
  • Optional Documents

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