Posted on Mon, 12/16/2024 - 12:51

Important Info

Faculty Sponsor (Last, First Name): 
Lo, Nathan
Stanford Departments and Centers: 
Med: Infectious Diseases
Postdoc Appointment Term: 
The position will be for a term of two years with the possibility of extension.
Appointment Start Date: 
Available immediately
Group or Departmental Website: 
http://profiles.stanford.edu/nathan-lo
/stanford-departments-and-centers/med-infectious-diseases
How to Submit Application Materials: 

Please submit the required application materials by email to Nathan.Lo@stanford.edu. Lab information can be found here: http://profiles.stanford.edu/nathan-lo. Review of applications will be performed on a rolling basis and continue until the position is filled.

Does this position pay above the required minimum?: 
Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.
Pay Range: 
$75,000-80,000

The Lo Lab at Stanford University seeks skilled postdoctoral scholars to join our research team. Specializing in infectious disease epidemiology and public health modeling, we study vaccine-preventable infections (e.g., SARS-CoV-2, pertussis) and neglected tropical diseases (e.g., schistosomiasis, strongyloidiasis). Our research group is interested in the transmission of infectious diseases and impact of surveillance and public health interventions with an overarching goal of informing public health policy. The postdoctoral scholar will have the opportunity to lead high impact research in infectious disease epidemiology and modeling across multiple pathogens. The work will have broad scientific and public health impact in infectious diseases.

 We are recruiting for postdoctoral scholars with interests in neglected tropical diseases (particularly schistosomiasis) and/or vaccine-preventable infections. Our NIH-funded research on schistosomiasis leverages diverse epidemiologic modeling approaches to evaluate precision surveillance and control strategies, with an emphasis on hotspot detection. This modeling work is well supported by large-scale primary datasets, including survey-based, parasitological, serologic, and genomic data. Relevant methodologies include mechanistic transmission modeling, statistical modeling, spatial data analysis, and cost-effectiveness analysis. In parallel, we conduct research on vaccine-preventable infections, developing and evaluating predictive modeling tools to support outbreak response, optimal vaccine strategies, and understanding key epidemiologic questions. This NIH-funded project is conducted in collaboration with the California Department of Public Health and focuses on pathogens such as SARS-CoV-2 and Bordetella pertussis, with opportunities to explore related infectious diseases and epidemiologic questions.

 The ideal candidate will have a superb quantitative background, strong coding skills (e.g., Python, R), expertise in infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high level of independence with publication record to support these characteristics. The postdoctoral scholar may work alongside students in the laboratory. 

 The lab will support and encourage the candidate’s independent research interests that align with our mission. Beyond this position, we welcome applicants proposing interesting scientific directions in infectious disease modeling broadly and will fund a highly independent postdoctoral scholar with a clear vision of scientific investigation that falls within the lab’s mission.

 Our Division of Infectious Diseases and Geographic Medicine encompasses all aspects of infectious diseases research and provides a strong community of scientific colleagues and students. 

Required Qualifications: 
  • The ideal candidate will have a PhD in Epidemiology, Engineering, Data Science, Applied Mathematics, Statistics or related computational field.
  • Superb quantitative background, strong coding skills (e.g., Python, R).
  • Expertise in infectious disease modeling.
  • Strong record of peer-reviewed publications. 
  • High level of independence in scientific work.
  • The successful candidate will be mission driven, hardworking, and motivated by the potential for scientific and policy impact, especially to improve health equity.
  • Enthusiastic about infectious diseases and global public health.
Required Application Materials: 
  • Cover letter that describes your research interests, scientific skillset and its alignment with the proposed work, and future career plans
  • Curriculum vitae
  • Contact information for three references

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.