Applications are invited for an NIH-funded Postdoctoral Associate position. We are looking for scholars with experience in data analysis. In the scope of this project, we will uncover how the human genome variation maps to disease. Specifically, we will be looking at whole exome variation of healthy individuals vs. disease-affected patients. The position will involve developing new computational algorithms to (1) mine the available scientific databases and literature for experimentally established disease genes, variants, and pathways/networks (2) predict functional effects of individual genetic variants, and (3) probabilistically annotate disease predisposition on the basis of the combinations of individual variant effects. The expected outcome of this effort is a novel computational pipeline for generating hypotheses of variome to disease correlation. Although we expect our methods to generalize to a range of disorders, we are particularly interested in the study of Crohn's disease, Chronic Obstructive Pulmonary Disease (COPD), and Tourette Syndrome.
The Bromberg lab develops and maintains computational tools for the analysis of the genetic variation. We are part of the National Institutes of Mental Health Center at Rutgers University. In the scope of this project, we collaborate closely with the Tischfield lab in the Department of Genetics, which provides excellent molecular biology and genetics expertise, as well as full access to the scientific resources of the Rutgers Cell and DNA Repository (RUCDR). As a board member, Dr. Bromberg has access to the computational resources of the Informatics Discovery Institute at Rutgers (RDI2). As a fellow of the Institute of Advanced Studies in Technical Institute of Munich (TUM-IAS), Dr. Bromberg also collaborates extensively with the members of the TUM department of Bioinformatics and Computational Biology.
Minimum Education and Experience:
Candidates should have a PhD in Computational Biology, Bioinformatics, Computer Science (w/biology background) or Genetics (w/computational background). We strongly encourage recent PhD graduates to apply. Programming skills are essential, as well as some familiarity with the major bioinformatics tools/databases.
Required Knowledge, Skills, and Abilities:
Experience with high performance computing, machine learning, and whole genome data analysis is desired, but not required. Computationally oriented candidates from labs studying the genetics of psychiatric or auto-immune disorders will be given preference. Applicants should be fluent in spoken and written English and should be able to communicate ideas and results to colleagues. The ability to integrate into a team is as essential as that to complete a project without constant supervision.
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