Description: Postdoctoral positions are available in the labs of Dr. Eran Agmon and Dr. Pedro Mendes at the University of Connecticut School of Medicine. These positions are in the field of computational systems biology and focus on the development of biological models and simulation software.
As part of the Agmon lab (https://eagmon.github.io/), the postdoctoral fellow will build integrative models of cellular systems. This will involve working on one or more projects in whole-cell modeling (primarily E. coli), community interactions in microbiomes, synthetic cells, or the origins of life. This position would expand Vivarium (https://vivarium-collective.github.io) – a framework for multi-scale models that span from molecular underpinnings, to integrated cellular functions, to multi-cell interactions in dynamic environments.
As part of the Mendes lab (http://www.comp-sys-bio.org/index.html), the postdoctoral fellow will work on COPASI (https://copasi.org/) – a simulation software for biochemical dynamics. This position will focus on parallelization of optimization algorithms to accelerate parameter estimation of biochemical models. The postdoctoral fellow will interact both with the COPASI development team, which includes collaborators at the University of Virginia, as well as with the developers of Virtual Cell.
Workplace: The Center for Cell Analysis and Modeling (CCAM) at the UConn Health. CCAM is a multi-disciplinary research center focused on computational cell biology. We occupy an award-winning research building in the UConn Health campus in Farmington, Connecticut. The environment at CCAM is particularly rich in computational systems biology with researchers with expertise in a wide range of modeling approaches such as stochastic spatial modeling, rule-based modeling, and multi-scale modeling. At the same time, the proximity to basic biological scientists for a highly interdisciplinary environment with many cross-disciplinary collaboration.
Requirements: A PhD or equivalent in computational biology, bioengineering, computer science, physics, or related areas. Experience of programming, with preference for either Python or C++. Knowledge of parallel programming and use of GitHub resources would be especially appropriate. Previous experience of using systems biology simulation software is desirable but not essential.