Candidates must have a PhD in one of the following disciplines: biochemistry, molecular biology, computational biology, physics, or computer science. Additional work-related experience will be a plus. Computational candidates will require knowledge of standard computer languages, including Java, PERL, and C/C++. Excellent communication and writing skills and a strong analytical and quantitative background are essential. The ideal candidates will have experience either in (a) the experimental dissection of mammalian transcriptional and signaling pathways or in (b) the computational identification of putative Protein-DNA and Protein-Protein interactions using a diverse set of high-throughput data modalities, including microarray expression profiles, ChIP-Chip, sequence, and proteomics data.
Candidates possessing both backgrounds (experimental and computational) will be especially well suited to fill these positions. Computationally, the ideal candidate will have familiarity with processing large genomic data sets and with a variety of reverse engineering techniques, including optimization-based, statistical, and integrative approaches. Furthermore, the candidate will have familiarity with the kinetic models that are used to represent biochemical interactions in a cellular context, including transcriptional interactions, complex formation, and post-translational modification events, such as phosphorylation, acetylation, and ubiquitin-mediated degradation. Experimentally, the ideal candidate will be familiar with standard laboratory techniques, including Western and Northern blots, ELISA assays, mammalian cell culture (both for adherent and suspension cells), RT-PCR and quantitative RT-PCR, transfection, infection using lentivirus or adenovirus, and other such standard biotechnology methods. Furthermore, he or she will have familiarity with the isolation and labeling of mRNA for microarray expression profiling using the Affymetrix or the Agilent platform.
Send resume to: Andrea Califano at email@example.com AA/EOE
Students currently enrolled within a Master's or PhD program at the Center for Computational Biology and Bioinformatics (C2B2) or within the Department of Biomedical Informatics (DBMI) may further their educational pursuits by becoming a member of Dr. Califano's lab.