We currently have openings for graduate students and postdoctoral fellows in computational systems biology. In particular, we are looking for researchers interested in studying human disease and drug development using systems biology and genomic techniques. Specific positions are listed below. If you are interested, please email us at natelewis3 at gmail or n4lewis ucsd edu
Here in the Lewis laboratory at the University of California, San Diego, we are developing cutting-edge modeling and data analysis approaches to gain deeper insights into various human diseases and to improve biotherapeutic production. In particular we are expanding on genome-scale constraint-based modeling approaches to study metabolism and other processes associated with it. We are also developing novel approaches for big data analysis using systems biology, genomics, and genome editing. These approaches allow us to gain novel insights into diseases such as cancer, neuropathologies, congenital disorders of glycosylation, metabolic diseases, etc. In addition, we are developing tools to guide synthetic biology of Chinese hamster ovary cells for enhanced drug production.
Right now, we are seeking exceptional candidates interested in mammalian systems biology and drug development. The researcher in this position will work with a dynamic team of outstanding graduate students, postdocs, and other researchers in the Lewis lab. The fellow will work in our group to help develop computational algorithms and genome-scale models of metabolism and protein secretion, and apply these to identify targets for disease treatment and drug development. In addition, she or he will be expected to take the lead in preparing manuscripts, presentations, and patents. This work will leverage experience in bioinformatics, genomics, metabolomics, glycomics, and/or constraint-based modeling. Necessary skills include an ability to operate in Linux-based systems and experience in programming languages such as MATLAB and/or Python. Interested candidates are encouraged to contact Nathan Lewis at n4lewis ucsd edu.
Over the past two decades we have seen great strides in our ability to simulate complex biological systems, even down to the molecular scale. However, the multiscale nature of higher eukaryotes has made it difficult to build accurate models of molecular processes in humans. Thus in collaboration with labs at the University of Virginia and Harvard Medical School, we are embarking on the development of a model that integrates single cell sequencing and targeted genetic perturbations to build a multicellular model of a whole higher eukaryote. This project will require the ability to work with next-gen sequencing data and genome-scale metabolic models. Furthermore, novel algorithms and modeling schemes will be developed in the process.
Autism is a highly heterogeneous disorder at both phenotype and genotype. Indeed, the genetic variants most strongly associated with autism account for only a very small set of all cases. Therefore it is likely that at the molecular level, many different genes may converge on similar molecular pathways to guide the development of the autistic phenotype. We are now seeking exceptional candidates interested in analyzing transcriptomic and clinical data of hundreds of children to develop network-level biomarkers for autism diagnosis and prognosis. The researcher in this position will work with a dynamic team of outstanding graduate students, postdocs, and other researchers in the Lewis and Courchesne labs at UCSD. She or he will be expected to take the lead in preparing manuscripts, presentations, and patents. This work will leverage experience in bioinformatics, genomics, transcriptomics, systems biology, and machine learning. Necessary skills include an ability to operate in Linux-based systems and experience in programming languages such as MATLAB and/or Python. Interested candidates are encouraged to contact Nathan Lewis at n4lewis ucsd edu.