February 2018. We are seeking a computational postdoctoral fellow to drive a research program on search engines for genomic data. The Langmead Lab, together with other labs at JHU (e.g. Leek, Hansen, Jaffe) and OHSU (Nellore) have developed tools (Rail-RNA, Snaptron) and resources (recount2) that altogether constitute a powerful search engine for public RNA sequencing data. The fellow will take these efforts to the next level and apply them to new data types and scientific questions.
The fellow should have experience in areas relevant to the lab’s agenda, e.g. (a) efficient software for analyzing high-throughput biological data, especially sequencing data, (b) scalable software for analyzing many datasets at once, and (c) indexing, sketching and other techniques for making large datasets — raw or summarized — easy and efficient to query.
Prospective graduate students interested in computational genomics are encouraged to apply to the graduate program in the Department of Computer Science at Johns Hopkins University. Both Masters and Ph.D. programs are offered. The Langmead Lab is seeking new PhD students to start in 2018. Our lab has ongoing projects in (a) fast and memory-efficient algorithms for analyzing DNA sequencing data (Bowtie, Bowtie 2, HISAT), (b) cloud computing and scalable software tools for analyzing large collections of public data (Rail-RNA, recount2, Snaptron), (c) machine learning for improved characterization of alignment uncertainty (Qtip), (d) methods for analyzing new sequencing data types.
Ph.D. students at JHU regularly take classes in other departments and collaborate across departmental boundaries. Please come, write great software, and collaborate with the excellent biomedical researchers at JHU!
Johns Hopkins has a large and diverse community of researchers studying methods and software for genomics. We are spread across diverse departments and centers including: