The American Museum of Natural History seeks highly qualified applicants for its Gerstner Postdoctoral Fellows program in Bioinformatics and Computational Biology. Successful applicants must be able to work effectively in applying innovative techniques to pursue independent and collaborative bioinformatics and computational research in integrative studies of genomics or spatial bioinformatics or biodiversity informatics, alongside faculty and other researchers interested in phylogenetics, phylogeography, evolutionary studies, and phenomics (the use of high-throughput computational methods to analyze morphological, physiological, and other phenotypic form and function). Fellows will also participate in the design, development and implementation of new algorithms, bioinformatics tools and infrastructure and computational methods to facilitate genomic assemblies and analyses, as well as developing methods to catalyze ongoing synthesis of phylogenetic information and address ‘big data’ issues from a computational perspective.
Applicants must have a PhD in Biological Sciences, Bioinformatics, Computational Biology, Computer Science, Molecular Biology, Genomics, or a related discipline, with experience in computational biology, bioinformatics, creating databases and computational pipelines, and analysis of large biological data sets. Proficiency in programming and scripting required (ideally Python, Perl, and R), and familiarity with other languages, such as mysql, C++/C, or Java, is desirable. For bioinformatics and computational biology tool development, candidates should have documented skills in various areas of expertise, such as next-generation sequence processing (quality screening and error correction), de novo and reference guided assembly for non-model eukaryotic whole genomes and transcriptomes, read mapping, gene annotation and discovery, and/or processing phenomic, transcriptomic, and phylogenomic datasets. Experience in a bioinformatics setting and in operating and maintaining high performance linux/unix servers preferred. Candidates should have extensive research experience with a solid publication record, ideally with some experience in phylogenetic methods, and excellent interpersonal, writing and problem-solving skills.
