Postdoctoral Position, Department of Engineering Sciences and Applied Mathematics

A postdoctoral position is available in Dr. Niall Mangan’s group in the Dept. of Eng. Sci. and Applied Mathematics at Northwestern University. The work aims to perform data-driven model construction and reduction for biological systems in direct collaboration with synthetic biologists. The goal is to rapidly characterize engineered biological systems to accelerate biomanufacturing. The postdoc will combine machine learning, statistics, and active learning strategies to discover mechanistically interpretable models within a nonlinear, partial differential equation framework. Other career development opportunities include teacher training, lecturing classes, and mentoring students (none required). The position comes with a competitive salary, fringe benefits, and travel support.

A successful candidate will have a Ph.D. in a theoretical or computationally relevant area such as applied math, applied physics, engineering, computer science, or statistics. Most important is a research record demonstrating strong theoretical or computational skills and the ability to perform collaborative applied research.

Candidates with expertise in at least one of the following will be strongly considered:

1)        Numerical methods for nonlinear parameter estimation

2)        Modeling of molecular biological systems (metabolic or regulatory networks)

3)        Parameter Identifiability analysis for ODEs

4)        Applied information geometry

5)        Model selection methods such as sparse regression

A single candidate is not expected to have all the skills they will need for this research coming in the door, however they are expected to have enthusiasm for bridging research domains and learning new methods.

To apply, please send a short cover letter explaining your interest in the position and CV to niall.mangan@northwestern.edu  Include the contact information for 3 references and indicate your most relevant publications in the CV. Candidates will be reviewed on a rolling basis starting November 15th.