NRL’s Center for BioMolecular Science and Engineering has multiple research opportunities available in the fields of Computer Engineering, Software Engineering, and Bioinformatics. Successful candidates will have obtained a Ph.D. degree in computer science, computer engineering, computational biology, biochemistry, chemistry, life sciences, or closely related fields within the past five years and full US citizenship. Demonstrated expertise in large-scale data analyses via database querying (such as SQL, mongoDB, noSQL), scripting for processes automation and routine tasks (Python, bash, Perl), programming proficiency (in C, C++, and/or Java), and familairity with Linux environments is expected. Candidates with previous expertise in artificial intelligence or machine learning will be considered. Highly desirable skills for candidates include demonstrated expertise on Cloud Computing platforms with encoded data formats (such as Apache Parquet).  

It is essential that candidates are highly motivated, independent, organized, and have direct experience in analyzing, presenting, communicating, and reporting results of their work through the peer review process.  

Candidates will be joining a highly multidisciplinary team of scientists engaged in systems and synthetic biology research.  Potential projects involve engineering of compute environments for large-scale analyses of '-omics' measurements (eg. genomes, transcriptomes, proteomes, and metabolites), tailored to the candidates background experience and career goals.  

Interested candidates should directly email judson.hervey<at>nrl.navy.mil for more information.  

NRL is an Equal Opportunity Employer.        

Representative References:     

Ghurye J, Treangen T, Fedarko M, Hervey WJ, Pop M.  MetaCarvel: linking assembly graph motifs to biological variants.  Genome Biology. 20 (1), 174.  2019.  Special edition on Microbiome Biology.  DOI: 10.1186/s13059-019-1791-3

Blank C, Easterly C, Gruening B, Johnson J, Hervey WJ, Nunn BL, Griffin TJ, Jagtap PD, et al.  Disseminating metaproteomic informatics capabilities and knowledge using the Galaxy-P framework.  Proteomes.  6:1.  2018.

Guo X, Li Z, Yao Q, Mueller RS, Eng JK, Tabb DL, Hervey WJ, Pan C.  Sipros Ensemble improves database searching and filtering for complex metaproteomics.  Bioinformatics (Oxford).  Volume 34, Issue 5, 01 March 2018, 795–802. 

key words

Computer science; Bioinformatics; High performance computing; Systems biology; Synthetic biology Genomics; Mass spectrometry-based proteomics; Software engineering; Computational biology; computer engineering

Citizenship:  Open to U.S. citizens and permanent residents

Level:  Open to Postdoctoral applicants