Training

Inspiring and developing the next generation of scientists is core to our mission. We do this locally and internationally through invested mentorship, a focus on scientists at all levels, and by creating a dynamic interdisciplinary environment where we all learn from each other. Applicants representing historically underrepresented backgrounds are encouraged to apply.

EPPIcenter logo

 

**SEEKING Postdoc** Malaria genomic epidemiology and transmission networks

The EPPIcenter at UC San Francisco is seeking a talented scientist to study the transmission of malaria using genomic and epidemiologic data. The successful candidate will be immersed in the multidisciplinary research environment of the Experimental and Population-based Pathogen Investigation center (EPPIcenter.ucsf.edu) and work closely with Drs. Bryan Greenhouse and Isabel Rodriguez-Barraquer along with a diverse team of scientists at UCSF and international collaborators. The fellow will be expected to develop and extend computational methods for deriving epidemiologically relevant information on malaria transmission from genetic, spatial, and epidemiologic data, and will be encouraged to develop an independent line of work under the co-mentorship of Rasmus Nielsen (U.C. Berkeley). 

read more about this opportunity

Our team is directly involved in all aspects of data generation and analysis including field work, generating laboratory data, modeling, communicating directly with malaria control programs in endemic countries, and building research capacity. Competitive salary including full benefits will be provided commensurate with experience and qualifications, and the post offers ample opportunities for career development.

Essential Skills

PhD or equivalent in a relevant field
Background in phylodynamics, epidemiologic modeling, and/or transmission dynamics
Strong statistical and computational skills

Demonstrated ability to produce independent, creative work
• Ability to work well as member of a team
Excellent written and oral communication skills
• Excellent written and oral communication skills

Helpful Skills

Background in basic biology, population genetics, ecology, and next generation sequencing data
Experience in analysis/modeling of infectious diseases
Programming experience in in C++

**SEEKING Postdoc/Research Scientist**  Modeling public health policies in infectious diseases

We are recruiting for one full time position, either a post-doctoral scholar or research scientist, who is interested in working on computational public health research related to infectious diseases. The project would focus on developing computational models to improve infectious disease surveillance, control strategies, and public health decision making. There are many ongoing projects related to COVID-19, hepatitis A, and neglected tropical diseases.

read more about this opportunity

The research group of Dr. Nathan Lo at UCSF uses computational modeling to inform and change public health policy in global infectious diseases. We mix fields of statistical modeling, simulation, epidemiology, and genomics to guide pressing policy issues. Past projects have included mathematical modeling of new World Health Organization guidelines for treatment of parasitic worm infections that affect 1.5 billion of the world’s poorest people, simulation of asymptomatic testing strategies for control of COVID-19 during the pandemic, outbreaks in vulnerable populations such as detained migrants, and work on guidelines for vaccine-preventable infectious diseases such as typhoid fever and measles. We have published in the top journals (Lancet and JAMA journals, PNAS, NEJM) and have been featured in media outlets (New York Times, The Guardian). Our track record includes many projects in infectious diseases that have translated into policy change and practice, including in the fields of neglected tropical disease and HIV. We work closely with policy organizations like the World Health Organization and the California Department of Public Health to ensure our research translates to improvements in human health. Our group works in a collaborative team environment, both within our research group and also as part of the UCSF EPPIcenter program, a dynamic team of basic science and computational scientists focused on understanding infectious diseases.

The position requires the following:
• PhD in epidemiology, statistics, engineering, computational biology, computer science, or related field. Highly qualified applicants with Bachelor's or Masters degree may apply.
• Strong programming skills in at least one of the following languages (R, MATLAB, Python)
• Strong quantitative skills, including statistical modeling, decision science, simulation, intermediate biostatistics, and basic mathematics
• Knowledge of epidemiology and population health measurement
• Ability to work independently and execute research projects with minimal supervision
• Excellent communication skills (e.g. data visualization, writing)


You will work in the research group of Dr. Nathan Lo (http://profiles.ucsf.edu/nathan.lo) in the Division of HIV, Infectious Diseases, and Global Medicine at UCSF. Our research group is part of the UCSF EPPIcenter program. Competitive salary including full benefits will be provided commensurate with experience and qualifications. The start date of the position is flexible, and applications are considered on a rolling basis.​​​​

To Apply:

Please send a CV including publications, brief statement of research/career interests, and contact information for 3 references to [email protected]. We are always looking for excellent candidates! Positions are open until filled, apply promptly.

                 Drs Greenhouse & Rodruiguez drawn as Simpsons characters

 

 Click here to check out the photos from our lab
Lab members Aug 2020
August in San Francisco- yes, it's that cold
Lab members meet socially
Social... before the distancing...
​​​​
July 2020 lab people
July 2019 lab people
Lab at the escape room
Escape room!

 

Stay in touch- subscribe to our quarterly updates

E-mail us subscribe to quarterly news review past newsletters