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Are you looking for a unique postdoctoral training that bridges algorithm development with cancer research? Derek Chiang's research group at the University of North Carolina is analyzing paired-end RNA-seq data on 2000 tumors per year for the NIH Cancer Genome Atlas project. We are interested in the mechanisms of alternative splicing alterations in cancer sub-types, especially on how aberrant DNA methylation in tumor genomes affects transcript diversity.
You will be working with a collaborative team of over 10 computer scientists, statisticians and molecular biologists to analyze 2nd and 3rd generation sequencing data. UNC features a highly supportive training environment for basic and translational cancer research, a bioinformatics core facility, and an expanding sequencing infrastructure (8 Illumina HiSeq 2000 and a PacBio SMRT sequencer).
Funding is guaranteed for two years, and you will be encouraged to apply for career development awards.
Qualifications
A PhD degree in Bioinformatics, Computer Science, Molecular Biology, Statistics, or related discipline with strong programming skills as well as a solid understanding of statistical methods. The ideal candidate has a track record of innovative analyses for genome-wide data, as evidenced by first author publications.
Contact
Please send a CV, list of three references and a short letter of research interests to:
[email protected]
Selected Publications
1. Singh D, Orellana C, Hu Y, Jones CD, Liu Y, Chiang DY, Liu J, Prins JF (2011). FDM: A graph-based statistical method to analyze differential transcription using RNA-seq data. ISMB HiTSeq Satellite meeting, 2011.
2. Hu Y, Wang K, He X, Mieczkowski P, Savich GL, Chiang DY, Prins JF, Liu J (2010). A probabilistic framework for aligning paired-end RNA-seq data. Bioinformatics, 26(16): 1950-7.
3. Wang K, Singh D, Zeng Z, Coleman SJ, Huang Y, Savich GL, He X, Mieczkowski P, Grimm SA, Perou CM, MacLeod JN, Chiang DY, Prins JF, Liu J (2010). MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Research, 38(18): e178.
4. Chiang DY, Getz G, Jaffe DB, O'Kelly MJ, Zhao X, Carter SL, Russ C, Nusbaum C, Meyerson M, Lander ES (2009). High-resolution mapping of copy-number alterations with massively parallel sequencing. Nature Methods, 6(1): 99-103.
You will be working with a collaborative team of over 10 computer scientists, statisticians and molecular biologists to analyze 2nd and 3rd generation sequencing data. UNC features a highly supportive training environment for basic and translational cancer research, a bioinformatics core facility, and an expanding sequencing infrastructure (8 Illumina HiSeq 2000 and a PacBio SMRT sequencer).
Funding is guaranteed for two years, and you will be encouraged to apply for career development awards.
Qualifications
A PhD degree in Bioinformatics, Computer Science, Molecular Biology, Statistics, or related discipline with strong programming skills as well as a solid understanding of statistical methods. The ideal candidate has a track record of innovative analyses for genome-wide data, as evidenced by first author publications.
Contact
Please send a CV, list of three references and a short letter of research interests to:
[email protected]
Selected Publications
1. Singh D, Orellana C, Hu Y, Jones CD, Liu Y, Chiang DY, Liu J, Prins JF (2011). FDM: A graph-based statistical method to analyze differential transcription using RNA-seq data. ISMB HiTSeq Satellite meeting, 2011.
2. Hu Y, Wang K, He X, Mieczkowski P, Savich GL, Chiang DY, Prins JF, Liu J (2010). A probabilistic framework for aligning paired-end RNA-seq data. Bioinformatics, 26(16): 1950-7.
3. Wang K, Singh D, Zeng Z, Coleman SJ, Huang Y, Savich GL, He X, Mieczkowski P, Grimm SA, Perou CM, MacLeod JN, Chiang DY, Prins JF, Liu J (2010). MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Research, 38(18): e178.
4. Chiang DY, Getz G, Jaffe DB, O'Kelly MJ, Zhao X, Carter SL, Russ C, Nusbaum C, Meyerson M, Lander ES (2009). High-resolution mapping of copy-number alterations with massively parallel sequencing. Nature Methods, 6(1): 99-103.