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Researchers for whole-cell computational modeling open

The Karr Lab at the Institute for Genomics & Multiscale Biology at the Icahn School of Medicine at Mount Sinai is seeking talented, ambitious researchers to develop cutting-edge whole-cell computational models of individual cells, as well as new technologies to enable larger and more accurate whole-cell models. Despite the explosion of experimental data, we do not understand the details of how phenotype arises from genotype and the environment. We are developing whole-cell computational models which comprehensively predict how behavior emerges from the molecular level by representing all of the biochemical activity inside cells. Our goal is to use whole-cell models to transform bioengineering and medicine into rigorous, quantitative disciplines. For example, we believe that whole-cell models could enable bioengineers to design microbial genomes for a variety of industrial applications, as well as enable physicians to tailor medical therapy to individual patients. Our research is highly interdisciplinary, involving systems biology, genomics, bioinformatics, data integration, parallel simulation, optimization, software engineering, and data visualization, and highly team-oriented.

We are currently looking for team members in three areas:
  • Human whole-cell modeling. The candidate will develop a whole-cell model of human embryonic stem cells and use the model to gain insights into pluripotency maintenance among other fundamental cell behaviors. This will include aggregating and organizing experimental data, designing submodels, integrating submodels, fitting models, validating models, analyzing simulations, and using models to generate new hypotheses. There are also many opportunities to contribute to the development of new whole-cell modeling methods and tools. The candidate will work closely with our team at Mount Sinai, including our experimental collaborators.
  • Bacterial whole-cell modeling. The candidate will lead the development a whole-cell model of the reduced bacterium Mycoplasma pneumoniae and use the model to design more predictable, faster-growing, and non-virulent strains that could serve as chassis for future bioengineering such as a bacterial-based drug synthesis and delivery system. This includes expanding the scope of whole-cell models; improving the accuracy of whole-cell models; using new types of genomic data to train whole-cell models; systemizing the construction, representation, and simulation of whole-cell models; and developing new methods to use whole-cell models to design genomes. The candidate will work closely with our team at Mount Sinai, as well as our Minicell consortium experimental collaborators: Maria Lluch-Senar and Luis Serrano at the Center for Regulatory Genomics in Spain; Yonaton Arfi, Alain Blanchard, Carole Lartigue, and Pascal Sirand at the National Institute for Agricultural Research in France; and Jörg Stülke at the University of Göttingen in Germany. This project is supported by the NSF and ERASynBio.
  • Whole-cell modeling methods and technology development. To enable larger whole-cell models, including models of human cells, the Postdoctoral Fellow/Engineer will develop new methods for simulating large, multi-algorithmic whole-cell models. This will include developing a new algorithm for concurrently integrating mathematically heterogeneous submodels that share state and implementing this as a high-performance, parallel simulation software system. The Postdoctoral Fellow/Engineer would work closely with our team at Mount Sinai, as well as our parallel simulation collaborators Drs. Peter Barnes and David Jefferson at Lawrence Livermore National Laboratory and our broader international team of collaborators. The Postdoctoral Fellow/Engineer would also have many opportunities to work with our team to build and analyze whole-cell models.

Desired skills/experience
Whole-cell modeling is a highly interdisciplinary problem. Consequently, we're looking for people with a broad range of skills and experience. The ideal candidate has the following skills. Applicants with related experience are also encouraged to apply.
  • PhD in computational biology or related field;
  • Strong experience in dynamical and/or genome-scale modeling;
  • Broad knowledge of cell biology, genomics, mathematics, and computer programming;
  • Deep commitment to innovation and desire to tackle the most challenging problems;
  • Abilities to solve challenging problems by thinking creatively, integrating diverse concepts, and pushing through barriers;
  • Passion for transforming bioengineering and medicine;
  • Excellent oral and written communication skills; and
  • Abilities to work independently and within a team.
Commensurate with experience and education.

All employees are eligible for medical, dental, and health insurance. Subsidized housing is available for postdoctoral fellows.

About the Institute for Genomics & Multiscale Biology and the Icahn School of Medicine at Mount Sinai
The Icahn Institute for Genomics & Multiscale Biology is a leader in basic and translational genomic and computational biology research. The institute's multidisciplinary researchers bring state-of-the-art genomic technologies together with advanced computational analyses to discover new disease mechanisms, develop new diagnostics, and identify new drug targets. The institute is a highly collaborative and interdisciplinary environment. Please see the institute's website  for more information.

The Icahn School of Medicine at Mount Sinai is a world leader in translational medicine. The school's multidisciplinary research institutes foster collaboration along a seamless continuum from the laboratory to patient care. State-of-the-art laboratories support groundbreaking research, and abundant clinical venues offer superb patient care and training.

More information
Please see our website (http://www.karrlab.org/join) or contact Jonathan Karr (http://www.karrlab.org/contact).

How to apply
Please email a cover letter outlining your research interests and a CV to Jonathan Karr (http://www.karrlab.org/contact).

posted 2016.07.12