The Cellular Engineering laboratory integrates multidisciplinary methods to understand the basic principles underlying cell functions in order to modify and build cells with designed activity. For this purpose, we have access to several IBM supercomputers, which are among the fastest in the world. The laboratory 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. The candidate will work in close collaboration with world known scientists.

 

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 underlying cell functions in order to modify 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 might include direct application of machine learning methods to cellular systems.

 

Interested candidates should contact Sara Capponi, PhD, ([email protected]) with a brief statement of research interest/cover letter, a CV, and contact information of 2-3 references. Students in their final year of Ph.D. training are encouraged to apply.

 

 

Qualifications:

 

    • PhD in Computational Biology, Computational Biophysics, Physics, Bioengineering or related field.

    • Experience in chemistry, physics, engineering, computer science, computational biology, or related fields.

    • Experience in computational modeling methods.

    • Experience in machine learning, deep learning packages.

    • Proven experience with python programming.