[BioC] Postdoctoral positions at Harvard

Edo Airoldi airoldi at fas.harvard.edu
Fri Jul 30 17:16:28 CEST 2010


Several postdoctoral positions are available in Statistics, Machine  
Learning, and Integrative Genomics within the Department of  
Statistics, and the FAS Center for Systems Biology at Harvard  
University, under the supervision of Professor Edo Airoldi.

We are seeking outstanding postdoctoral candidates from statistics,  
machine learning, and computational biology, to work on several newly  
funded projects in these areas, including but not restricted to:

(A) Developing new methods and theory for statistical representation,  
sampling and inference of large-scale biological and information  
networks.

(B) Developing new methods and theory for systems level analyses of  
regulation and signaling dynamics, with applications to yeast, stem  
cell development and cancer systems.

More details of the projects are available at www.fas.harvard.edu/~airoldi/

We encourage in-coming postdoctoral fellows to explore the other  
projects listed on this page, and initiate new projects. Edo Airoldi’s  
research group offers a highly energetic interdisciplinary environment  
for working on a wide range of challenging theoretical and applied  
problems in statistical learning and computational biology. We work  
closely with clinical and biological laboratories in the Harvard  
Medical School, MIT, The Broad Institute, NYU, Princeton, University  
of Cambridge, and other schools to address various problems of  
practical medical and biological
interests. Successful candidates will have opportunities to interact  
with world-class researchers in all the areas mentioned above and  
beyond. Cambridge is an exciting place with rich intellectual,  
cultural and recreational resources, and a vibrant living environment.  
We offer competitive salary and benefits.

The ideal candidates should have a strong track record of research in  
machine learning, statistical genetics, and computational systems  
biology, evidenced by high quality publications; be able to  
communicate and work with collaborating student/postdocs and external  
PIs; and be able to carry out research and develop ideas  
independently. Good programming skill and solid statistics/math  
background are highly desirable.

How to apply. Send curriculum vitae, contact information (phone/email)  
for three references, a research statement, and 1-3 publications/pre- 
prints to Ms. Dale Rinkel (rinkel at stat.harvard.edu) at Department of  
Statistics, Harvard University, 1 Oxford Street, Cambridge, MA 02138,  
USA.

Email applications should also be copied to Prof. Edo Airoldi (airoldi at fas.harvard.edu 
)



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