The Cellular Engineering lab integrates multidisciplinary methods to understand the basic principles underlying cell functions in order to modify and build cells with designed activity. Our focus is to leverage AI/ML methods for harnessing the power of cells and develop powerful predictive models of cellular structure and function. The candidate is expected to integrate and develop novel AI/ML algorithms to understand the basic principles governing cells in order to modify them and build cells with designed activity. The ideal candidate should have strong background in computational biology and modeling, biophysics, AI/ML methods for biological system analysis and cellular dynamics. Relevant areas of expertise include direct application of machine learning methods to cellular systems.
The Cellular Engineering lab is part of the NSF Center for Cellular Construction in partnership with UC San Francisco, UC Berkeley, Stanford University, SF State University, and the SF Exploratorium. The overall goal of the Center is to develop an engineering discipline to design cells. For this purpose, we have access to several IBM supercomputers, which are among the fastest in the world. The candidate will work in close collaboration with world known scientists.
Interested candidates should contact Sara Capponi, PhD, (sara.c...@ibm.com) with a cover letter, a CV, and contact information of 2-3 references. Students in their final year of Ph.D. training are encouraged to apply.
Required Skills: 1) PhD in Computational Biochemistry or Biology, Chemistry, Physics, Bioengineering, or related fields. 2) proven experience with mathematical modeling, statistical analysis, and AI/ML methods applied to biological data and systems. 3) Demonstrated experience with collaborators and experimentalists. 4) background in molecular dynamics simulations and computational modeling of proteins and biological systems.
Preferred Skills: 1) Experience in biology, physics, mathematics, chemistry, computer science, or related fields. 2) prior experience with python programming or other languages and data analysis. 3) good publication record. 4) Excellent English communication (written and oral). 5) Fully dedicated and self-motivated.