Position Title: POSTDOCTORAL / RESEARCH ASSOCIATE POSITION IN COMPUTATIONAL / STATISTICAL GENOMICS

Duties & Responsibilities: A computational post-doctoral (or research associate) position is available in an interdisciplinary research group led by Dr. *Roger Pique-Regi* and Dr. *Francesca Luca* at the Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI; and in close collaboration with Dr. *Xiaoquan Wen*, Department of Biostatistics, University of Michigan, Ann Arbor, MI. The research focus of this team is on understanding the genetic and molecular characterization of gene regulation. Examples of projects include: characterizing variation in the gene expression response to hormonal and environmental stimuli, identifying tissue-specific cis-regulatory modules with DNase-I footprinting, and detecting signals of selection and adaptation in gene regulatory regions. The ultimate aim is to learn about the genetic basis of disease susceptibility and response to treatment. We have a strong record in using both *functional and evolutionary genomics* approaches. We use a combination of high throughput experimental platforms and advanced computational/statistical tools. We seek applicants who are very creative, energetic, and can work independently. We operate relatively small but well-funded and intense laboratories. Our policy is that each fellow in our team should have the resources, support and mentorship needed to be successful and become an independent investigator.

Position Qualifications: We are looking for very talented individuals with a strong *computational and/or statistical background*. Applicants should have a publication record demonstrating the development of novel quantitative/statistical methods, and have a strong interest in genomics. A background in computational biology, bioinformatics or statistical genetics is an advantage, although we will also strongly consider outstanding candidates with quantitative degrees (e.g. in Statistics, CS, or Engineering) but less genetic/genomics experiences. Excellent programming skills in C/C++, and scripting languages like Python/Perl is a requirement, as well as having experience in developing advanced statistical machine learning methods such as: expectation maximization (EM), hidden Markov models (HMMs), and Markov chain Monte Carlo (MCMC). Working knowledge with next generation sequencing data analysis tools (e.g. BWA, Bowtie, MACS, TopHat and Bed/VCF/Sam-tools and Samtools) is an advantage, but transferable experience with “big-data” methods from other fields (e.g., HDF5, Wavelets, Signal/Video Processing, Sparse models, large matrix factorization) will also be valued. Salary will be very competitive and commensurate with the applicants’ experience/abilities.

Salary Range:

Benefits:

Web Site: http://cmmg.biosci.wayne.edu/edunew/faculty/regi/index.html

Application Address: For more information please contact: Roger Pique-Regi, PhD e-mail: rpique@wayne.edu Francesca Luca, PhD e-mail: fluca@wayne.edu To apply, send a cover letter that describes your background, motivation, and interests accompanied by a full CV to rpique@wayne.edu and luca@wayne.edu. Please, also arrange to have 3 letters of recommendation to be sent directly by the letter writer to the above email addresses.

Contact Email: rpique@wayne.edu; fluca@wayne.edu

Application Deadline: 01/01/2013