Postdoctoral Research Associate - Statistical Analysis
The Department of Astrophysical Sciences, Princeton University has as an open postdoctoral or more senior research position in the area of statistical analysis of wide-field survey data, working with Peter Melchior and the Princeton Astronomical Data Group (led by Robert Lupton, Michael Strauss and Jim Gunn). The group is deeply involved in the Large Synoptic Survey Telescope (LSST), the Hyper Suprime Cam and Prime Focus Spectrograph instruments on the Subaru Telescope, and the space-based Wide Field Infrared Survey Telescope (WFIRST). We encourage applications from those working in astronomy and physics, computer science, statistics, applied mathematics or other pertinent fields. We look for individuals with expertise that strengthens or complements existing research directions in the Astronomical Data Group. Prior experience with astronomical image analysis or relevant inter-disciplinary approaches should be clearly outlined in the application. Of particular interest are techniques for multi-band and multi-resolution image analysis to detect, classify, and deblend celestial objects, novelty detection, and efficient representation of galaxy morphologies and colors. The ideal candidate would have a strong research record, a collaborative spirit, and experience with software development in python or C/C++. PhD in a related field is required. Appointments are for a period of one year, but our expectation is that the appointment would be renewed for a total of three years, assuming satisfactory research progress and availability of funding. The start date can be negotiated, with a preference for early commencement. We are seeking to recruit from as diverse a pool of talent as possible, and endeavor to preserve the Astrophysical Sciences Department's reputation as a pleasant workplace with a lively and friendly scientific atmosphere which recognizes that innovations in the analysis of astronomical data are central to the science produced by major astronomical surveys. Applicants must apply online and submit a CV, a concise (max. 3 pages) description of relevant past research achievements and future plans, and contact information for three references at [Princeton URL]. Letters of recommendation will also be handled through this site. All applications received by November 1, 2017 will be fully considered, but applications will continue to be accepted until the position is filled. This position is subject to the University's background check policy. For further inquiries, contact Peter Melchior (firstname.lastname@example.org).