Develop mathematical & statistical models to explore ID epidemiology, immunity development, control strategies & public health decision making.

Recruiting post-docs who will work on highly interdisciplinary projects on infectious disease epidemiology and dynamics. We are seeking to hire highly motivated and independent post-doctoral scholars to join the EPPIcenter (Experimental & Population-based Pathogen Investigation Center) at the University of California, San Francisco, with Drs. Bryan Greenhouse and Isabel Rodríguez-Barraquer. The goal of our research center is to understand complex infectious disease dynamics by integrating state-of-the-art data collection, molecular technologies, and computational analysis. Our interdisciplinary approach provides novel insight into the targeting of interventions to reduce and ultimately
eliminate infectious disease burden.

Our portfolio includes many projects in infectious diseases that have translated into policy change and practice, including in the fields of malaria, dengue, neglected tropical diseases, and COVID-19. We work closely with policy organizations like the World Health Organization, California Department of Public Health, and Ministries of Health to ensure our research translates to improvements in human health. Our group provides a diverse and vibrant collaborative team environment with an emphasis on mentorship and career development.

Projects involve development of mathematical and statistical models to analyze complex datasets (epidemiological and molecular) to answer questions in infectious disease epidemiology, development of immunity, control strategies and public health decision making.

Example projects/research areas include:

  • Developing and extending computational methods to reconstruct transmission networks and otherwise derive epidemiologically relevant information on malaria transmission from genetic, spatial, and epidemiologic data
  • Developing analytical pipelines for serosurveillance using novel multiplexed serological assays (focus on malaria and arboviruses)
  • Reconstructing emergence and transmission dynamics of arboviruses
  • Characterizing the development of strain specific immunity to malaria in the context of detailed longitudinal studies using genomics and high-throughput serological assays
  • Developing strategies for multi-pathogen disease intelligence, including emerging infectious diseases, in LMICs

Candidates interested in working on computational infectious disease research with a strong quantitative background are highly encouraged to apply.

Essential Skills
-PhD in epidemiology, statistics, math, physics, engineering, computational biology, computer science, ecology, public health, or related quantitative field. Exceptional predoctoral candidates with proven quantitative skills will also be considered.

  • Strong programming skills in at least one relevant languages, e.g., R, MATLAB, Python.
  • Strong quantitative skills, including statistical modeling, dynamic modeling, decision science, simulation, biostatistics, and basic mathematics.
  • Ability to work independently and execute research projects with minimal supervision.
  • Excellent communication skills, e.g., data visualization, writing.

Preferred
Prior background in epidemiology, ecology, population health measurement, and/ or infectious diseases

To Apply

Send a CV including publications, brief statement of research/career interests, and contact information for 3 references to EPPIcenter@ucsf.edu

Type
Postdoc
Institution
University of California at San Francisco UCSF
City
San Francisco
Country
USA
Closing date
February 28th, 2023
Posted on
November 1st, 2022 16:45
Last updated
November 7th, 2022 09:28
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