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Postdoctoral Training in Statistical Genomics

Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for contemporaneous advances in computation and mathematical modeling. As the complexity of genomic data sets drives innovative statistics research, the new Statistical Inference and Computation in Genomics (Statomics) Lab of the Ottawa Institute of Systems Biology seeks a postdoctoral researcher who will collaboratively develop and apply statistical methods to solve current problems in analyzing and integrating gene-expression, proteomics, metabolomics, SNP, ChIP-chip, and/or clinical data. The lab is presently targeting inference in genome-wide association studies, bias reduction in estimated levels of gene expression, and validation of microarray predictions and will attack similar statistical and computational challenges of importance to genetics and functional genomics. The researcher’s background will complement that of any students and any postdoctoral researcher to be recruited to the Statomics Lab from the biomedical and computer science communities, creating an interdisciplinary environment for high impact on the biological sciences as well as on statistics.

Scientific creativity and a thorough knowledge of either Bayesian statistics or another likelihood-based inferential framework are essential, as is the demonstrated ability to quickly and accurately implement likelihood-based methods in software. Strong initiative, excellent communication skills, and reception of a PhD in statistics or a closely related field within the four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: exposure to the law of likelihood; knowledge of biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.

To apply, send a PDF CV that has contact information of three references to dbickel0@uottawa.ca (without the zero), with “likelihood postdoc” and the year of your graduation or anticipated graduation in the Subject line of the message; in the plaintext message body, concisely include evidence that you meet each requirement for the position and a description of your most significant papers and software packages with an explanation of your own contributions to them. Only those applicants selected for further consideration will receive a response.

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