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 )