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.
We are interested in understanding chromatin structure and function in a variety of systems using high-throughput sequencing techniques. We specialize in analysis of ChIP-seq and nucleosome profiling data but also work with RNA-seq, whole-genome sequencing, and other data types. We collaborate with a number of experimental labs, both in the Harvard Medical area and around the world.
Integrative analysis of genomic data
We also engage in methodological research, developing new statistical and
computational algorithms and tools for understanding next-generation sequencing data. We aim
to address important problems and come up with efficient and
statistically valid methods that will have practical impact
on biological and clinical investigators.
Interested in joining the lab?
See the latest flyer for postdoctoral fellowship announcement!
NOTE: Please read the instructions on what to send. If you do not send the requested items, you will not receive a reply. Please note '[POSTDOC]' or '[GRAD]' in the subject line. If you do not hear back in one week, feel to send a reminder. Mass emails that do not meet basic requirements will not be acknowledged.
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 analysis of next-generation sequencing data, especially whole-genome sequencing data; ii) cancer genomics, combining data from expression, copy number, miRNA, SNP, methylation, and mutation sequencing; iii) chromatin structure and function using ChIP-seq data. In each position, the successful candidate will have an opportunity to work on new data sets from a fantastic group of experimental collaborators.
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. 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 firstname.lastname@example.org
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.