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DiSARM Research Specialist

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Position description

DiSARM Research Specialist

The University of California, San Francisco’s Institute for Global Health Sciences (IGHS) is dedicated to improving health and reducing the burden of disease in the world’s most vulnerable populations.

The Global Health Group (GHG) at UCSF’s IGHS, is an “Action Tank,” dedicated to translating major new paradigms into large-scale action to positively impact the lives of millions of people. Led by Sir Richard Feachem, formerly the founding executive director of the Global Fund to Fight AIDS, Tuberculosis and Malaria, the GHG works with researchers, policymakers and implementers to better understand and address health challenges and tackle neglected global health priorities. Through boldness, focus, collaboration and innovation, we can reduce the burden of disease and enhance economic prosperity for people around the world. The GHG’s Malaria Elimination Initiative (MEI) believes a malaria-free world is possible within a generation. The MEI brings the vision, strategy, and evidence-based approaches to catalyze action in countries and regions paving the way for global malaria eradication.

The MEI is seeking a Specialist. The specialist will be responsible for overseeing development and implementation of statistical analysis related to the Disease Surveillance And Risk Monitoring (DiSARM) project (www.disarm.io). DiSARM is a spatial intelligence tool that helps disease programs to better collect, visualize and analyze data to inform decision making. Currently DiSARM is used by several countries in southern Africa to help plan, implement and monitor indoor residual spray campaigns, with a forecasting module under development for Thailand. By consuming malaria case data, DiSARM is able to produce rapidly updateable risk maps using environmental/ecological layers. Similarly, machine learning algorithms can be used to distinguish residential from non-residential buildings. Other DiSARM projects include supporting the mapping and targeting of surveillance for loiasis and lymphatic filariasis in west and central Africa with proposed projects on TB and leprosy.

Specifically, roles of this position will include:

  • Identifying and processing relevant (spatial) predictors where required, such as remotely sensed environmental, climatological and ecological layers.
  • Developing and validating specific models/functions using R or Python programming languages, such as spatio-temporal models of infection prevalence/case incidence and machine learning classification algorithms.
  • Working with the DiSARM development team to make models/functions accessible via the DiSARM API
  • Supervising junior researchers within the DiSARM data science team
  • Contributing to the dissemination of results via reports, papers and presentations

Required Qualifications:

  • PhD in statistics
  • At least 5 years worth of experience dealing with spatial data and spatial statistics
  • Experience with Gaussian processes and machine learning algorithms
  • Experience with time-series analysis
  • Excellent working knowledge of python and R
  • Experience with 'git' platforms such as GitHub

Screening of applicants will begin immediately and will continue as needed throughout the recruitment period. Salary and rank will be commensurate with the applicants experience and training. Please apply online at https://aprecruit.ucsf.edu/apply/JPF01902.

UC San Francisco seeks candidates whose experience, teaching, research, or community service that has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.

Application Requirements

Document requirements
  • Curriculum Vitae - Your most recently updated C.V.

  • Cover Letter (Optional)

  • Statement of Research (Optional)

  • Statement of Teaching (Optional)

  • Statement of Contributions to Diversity (Optional)

  • Misc / Additional (Optional)

Job location

San Francisco, CA