The Kavraki Lab at Rice University (http://www.kavrakilab.org) develops computational methods and tools to model protein structure and function, understand biomolecular interactions, aid the process of medicinal drug discovery, analyze the molecular machinery of the cell, and help integrate biological and biomedical data for improving human health. The Lab provides a stimulating working environment and has an excellent record of placing postdocs in faculty positions. The Computer Science Department at Rice University is part of the Gulf Coast Consortia for Quantitative Biomedical Sciences (http://www.gulfcoastconsortia.org) and offers an unparalleled training environment.
The lab seeks candidates to fill one postdoctoral research associate position. The available project is on computational modeling of molecular interaction interfaces by integrating protein sequence and structural data. The overall goal of this research is (a) to develop novel methodologies for the analysis of peptide-HLAs, peptide-MHCs, and their recognition by CTLs, and implement these methodologies in toolkits that immunologists can use and (b) to tackle the more general problem of docking high-dimensional ligands into flexible receptors. Our research heavily uses machine learning methods and seeks to develop new computational methodologies for interpreting data in biology and medicine. The individual recruited to fill this position will work closely with collaborators at the MD Anderson Cancer Center and other researchers at the Texas Medical Center, the largest medical complex in the world.
Due to funding restrictions, this position is only open to US citizens or permanent residents.
The ideal candidate should have a strong enthusiasm for interdisciplinary work. Required skills include training in machine learning, excellent analytical skills, and strong experience with programming in Python. Prior knowledge of immunology is not required, but it is desirable. Familiarity with bioinformatics databases and tools is also desirable. A Ph.D. is required for the position in a related field. In the past, successful candidates had degrees in Bioinformatics, Computer Science, Bioengineering, Biophysics, Computational Biology, Physics, and Chemistry. Excellent communication and collaboration skills are required as the selected candidate will be expected to work closely with current lab members and collaborators.
Postdoctoral research associates are eligible for up to two years of support. All re-appointments are dependent upon a satisfactory progress review and continued funding.
Interested applicants should contact Professor Lydia Kavraki ([email protected]) and provide (a) a CV, (b) the names of three or more references, (c) a one-page description of their earlier work and (d) a one-paragraph statement about their interest in the advertised position.
The position is available immediately, and applications will be accepted until this position is filled.
Rice University is a private, comprehensive research university in the heart of Houston (recently ranked the most diverse city in America), adjacent to the Museum District and Texas Medical Center. It offers undergraduate and graduate degrees across eight schools and has a student body of approximately 8,000 undergraduate and graduate students. Rice consistently ranks among the top 20 national universities and the top 10 in undergraduate teaching (U.S. News & World Report); its endowment ranks among the top 20 US universities. The George R. Brown School of Engineering ranks among the top 20 undergraduate engineering programs and is strongly committed to nurturing the aspirations of faculty, staff, and students in an inclusive environment, with rankings of #8 for percent URM faculty, #14 for female faculty, and #4 for underrepresented undergraduate students among AAU institutions. Rice University is an Equal Opportunity Employer committed to diversity at all levels and considers for employment qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national or ethnic origin, genetic information, disability, or protected veteran status.