Postdoctoral Fellow: Eco-Evolutionary Malaria Modeling

New York University; New York (NY); On-site; USD 65,000 - 80,000; Full time

Job summary

New York University invites applications for a Postdoctoral Associate in the Pascual lab within Biology and Environmental Studies. The role focuses on the eco-evolutionary dynamics of host-pathogen systems and the population dynamics of vector-borne diseases, with a NIH-supported project on malaria diversity and resilience.

The ideal candidate has a PhD and strong modeling/programming background, with interest in connecting theory to epidemiological data and publishing results during the

Qualifications

• PhD required; prior research in theoretical ecology, epidemiology models, population genetics and evolution dynamics.
• Background in programming, applied mathematics and statistics.
• Experience with agent-based modeling, parameter estimation for high-dimensional systems or critical transitions is a plus.

Responsibilities

• Work with a stochastic agent-based model and perform parameter estimation from epidemiological and molecular data.
• Develop model formulations to simplify dynamics and explore transitions from high to low transmission/diversity.
• Collaborate with partners at University of Melbourne and NHRC to bridge theory with molecular and epidemiological data.
• Mentor and train while publishing research findings during the postdoc appointment.

Skills

Theoretical ecology

Mathematical modeling

Epidemiology

Population genetics

Evolutionary dynamics

Computer programming

Applied mathematics

Statistics

Agent-based modeling

Parameter estimation

High-dimensional systems

Critical transitions

Education

PhD

Job description

New York University invites applications for a Postdoctoral Associate in the Pascual lab within Biology and Environmental Studies. The role focuses on the eco-evolutionary dynamics of host-pathogen systems and the population dynamics of vector-borne diseases, with a NIH-supported project on malaria diversity and resilience.

The ideal candidate has a PhD and strong modeling/programming background, with interest in connecting theory to epidemiological data and publishing results during the