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Opportunity: Postdoctoral position in statistical genomics at UBC, Vancouver, Canada
Submitted by Raphael Gottardo; posted on Wednesday, May 07, 2008
BACKGROUND
FCM is proteomic technique that can be used for the identification of cell populations and/or for physically sorting and separating the cells. The technology is applied to many fields of science, including molecular biology, pathology, immunology, plant biology and marine biology. In the field of molecular biology it is especially useful when used with fluorescence tagged antibodies. These specific antibodies bind to proteins on or in the target cells and help to give information on specific characteristics of the cells being studied in the cytometer. FCM is integral part of proteomic and genomic technology. It has broad application in medicine (especially in transplantation, hematology, oncology, immunology, chemotherapy, and genetics). FCM can generate complex datasets both in terms of the number of parameters measured for each individual cell (over 20), as well as the number of individual cells analyzed per experiment (in the millions). As a result, the amount of data that is generated is enormous (gigabytes to terabytes), and the analysis is complex and very time consuming. Unfortunately, the bioinformatic and statistical tools available for FCM analysis have lagged behind other platforms like sequencing, arrays mass spectrophotometry etc. The objective of this project is to create new statistical tools able to take advantage of the high dimensionality of high throughput FCM (HT-FCM) data and to combine the result with genomics and proteomics. The methods proposed here will revolutionize the current basic academic and commercial tools in the scientific community.
RESPONSIBILITIES
The successful applicant will continue to develop our research program in the area of computational bioinformatics and statistics for flow cytometry. The candidate will be expected to participate in both methods development and data analysis, to work cooperatively with other lab members, to help maintain and improve the laboratory infrastructure (software, etc.), and to actively publish and present results. The successful applicant will also be expected to interact with the Brinkman lab at the BC Cancer Agency as well as collaborators in Seattle and Montreal.
REQUIREMENTS
The applicant must have a Ph.D. in biostatistics, statistics, computer science or related field (e.g. bioinformatics) with a strong background in statistics, a good computing background (C/Fortran, R/Matlab, ...) as well as a serious interest in molecular biology and genetics. The position is available immediately. The initial appointment will be for 1 year with the possible extension for a further 12 months. The review of applications will begin immediately and will continue until the position is filled.
COMPENSATION
A competitive salary commensurate with experience and skills will be offered, and a full benefits plan is available.
HOW TO APPLY
Interested candidates should send the following material directly to me (at raph[at]stat.ubc.ca): A cover letter highlighting your background and its relationship to this position; A Curriculum Vitae (CV), including a list of publications and a one-page outline of your previous research achievements; The names and contact details of at least three references.
DEADLINE
The position is available immediately. The initial appointment will be for 1 year with the possible extension for a further 12 months. The review of applications will begin immediately and will continue until the position is filled.
About the group

Our lab currently consists of the PI (Raphael Gottardo), one postdoc, 5 graduate students, plus several rotation students. Our main focus is the development of methods and software for the analysis of high throughput genomics data. For more information, see http://www.stat.ubc.ca/~raph.
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