POSTDOCTORAL POSITION IN STATISTICAL LEARNING AND DATA MINING FOR
GENE MAPPING

We seek a post-doctoral fellow that will work on a new
collaborative UCI/UCLA project on gene mapping, involving the
research groups of Professor Padhraic Smyth, Department of
Computer Science, University of California, Irvine, and Professors
Nelson Freimer and Chiara Sabatti, in the departments of Human
Genetics, Psychiatry, and Statistics at UCLA.

We have acquired and are in the process of acquiring a series of
unprecedented datasets with detailed genotypic and phenotypic
information. These datasets come from homogeneous population
isolates. Genotyping is being carried out on a genomewide basis
with high density SNPs. Phenotypes measured cover virtually every
organ system and have been collected on a longitudinal basis (see
Freimer and Sabatti, Nature Genetics 34:15-21, 2003). Mining these
data sets, we will investigate the definition of endophenotypes,
the presence of clusters among phenotypes, and their mapping to
locations in the genome. We will test the possibility of carrying
our genomewide association mapping for a variety of traits with
different characteristics and are interested in developing novel
methodology with this goal.

Competence in either genetic epidemiology and statistical
genetics, or in statistical learning and data mining are desirable
strengths in candidate applicants.

The expected duration of this position, funded by NIH, is two
years. The successful candidate will be expected to spend a
considerable portion of their time working at both UCLA and at UC
Irvine.

Prospective applicants should email a copy of their CV, names and
email contact information for at least 3 references, and a link to
online publications, to Padhraic Smyth at [EMAIL PROTECTED] Please
use "application for NIH postdoc position" in the subject line of
your email.

The University of California is an Equal Opportunity Employer committed
to excellence through diversity.
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