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Introduction
Recent technological developments have enabled researchers
to generate experimental data in an unprecedented, genome-wide
scale. Our aim is to gain biological insights through computational
and statistical analysis of genomic data.
Integrative analysis of genomic data
Methodological work: We develop new statistical and
computational algorithms and tools for understanding a variety
of data types, such as gene expression, array comparative
genomics hybridization, and Chromatin Immunoprecipitation/microarray
(ChIP-chip). We are particularly interested methods for combining
heterogeneous data sets to derive new insights. Our goal is
to address important problems and come up with efficient and
statistically valid methods that will have practical impact
on biological and clinical investigators.
Collaborative work: We work closely with several basic
and clinical research groups. We strive to maintain a close
and synergistic relationship through which we can address
important biological and methdological problems effectively.
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Open Positions (October, 2008):
We are always recruiting new members!
NOTE: Please read the instructions on what to send. If you do not send the requested items, you will not receive a reply.
Postdoctoral Fellowship:
Multiple post-doctoral fellowships in bioinformatics are available immediately to work in the laboratory of Dr. Peter Park at Harvard Medical School.
The long-term goal of the group is to understand gene regulation through computational analysis of genomic data, with focus on epigenetic aspects. Positions: i) statistical methods for combining multiple genomics data types; ii) cancer genomics, combining data from expression, copy number, miRNA, SNP, methylation, and mutation sequencing; iii) chromatin structure and function, using chip-seq/chip-chip data; iv) systems biology of organ regeneration, involving analysis of expression data and pathways. In each position, the successful candidate will have an opportunity to work on fantastic new data sets using the latest technologies including Solexa/SOLiD sequencing.
Ideal candidates will have a Ph.D. in a quantitative field and a substantial experience in analysis of genomic data. Excellent programming skills are essential and previous experience with R is a plus. Those who have applied previously are welcomed to apply again. The Harvard Medical area is one of the most exciting places in the world for biomedical research and our collaborators are among the top biologists.
Please send your CV, a brief statement of research interests, pdfs of your three best papers, and three letters of recommendations to peter_park@harvard.edu
Graduate Students
There are multiple openings for graduate students to work on the problems described above. The focus of the work will be computational; but, if desired, the student will have ample opportunity to carry out wet-lab work in one of the collaborating laboratories. Those with interest in epigenetics are particularly welcomed. NOTE: The student must already be enrolled in a graduate program at Harvard (Biophysics, Biological and Biomedical Sciences, or others) or at MIT (Health Sciences & Technology or others). Inquires regarding graduate student positions from those not already enrolled in one of these programs will go unanswered.
Undergraduate Research Assistants (MIT UROP or Harvard):
Multiple positions are open for undergraduates throughout
the year. A 10-hour commitment during the term and full-time commitment during summer are required. Strong quantitative
background and substantial programming experience are essential. Underclassmen with such experience are welcome to apply. You may also be interested in the Summer Institute in Bioinformatics and Integrative Genomics at Harvard-MIT Health, Science and Technology.
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