We are currently seeking a Post-Doctoral Scholar for a Computational Biologist/Dynamic Modeling position working in the area of measles and rubella epidemiology. The successful candidate will contribute to a project to process large-scale, public health surveillance datasets on measles and rubella incidence in sub-Saharan Africa and Asia and to develop dynamic models to evaluate candidate vaccination strategies for measles and rubella. This work will involve solving difficult problems in the fitting of large-scale, stochastic, age-structured dynamic models to high resolution public health surveillance data. The position is ideal for someone interested in working at the nexus of computer science, statistics, and biology. The skills that will be gained are in high demand in academia, the bio- and information-technology sectors, quantitative finance, etc.
The position requires a Ph.D in a quantitative discipline such as computational biology, population biology, epidemiology, computer science, statistics, physics, applied mathematics, engineering, etc. Additional qualifications include proficiency in at least one object oriented programming language -- e.g. Python or Java -- and experience building GUI and web-based applications using tools like WindowBuilder, Google Web Toolkit, and Java Web Start.
Preferred candidates will have experience in data visualization and a familiarity with the R language. Candidates should demonstrate a track record of publication; have strong organizational, written, and oral communication skills; and be able to work both independently and as part of a collaborative team.
This is a fixed-term position funded for one year from the date of hire, with excellent possibility of refunding. For further information, please feel free to contact Dr Ferrari (firstname.lastname@example.org; theferrarilab.com, +1 814- 865-6080). To apply, please send a copy of your curriculum vitae, a 1-2 page statement of research interests that explicitly describes your professional qualifications for this position, and contact information for three referees by email to Dr. Ferrari. Review of applications will begin immediately, and continue until the position is filled.
Employment will require successful completion of background check(s) in accordance with University policies. Penn State is committed to affirmative action, equal opportunity and the diversity of its workforce.