Sign up with your email address to be the first to know about new products, VIP offers, blog features & more.

PhD Opportunity in Machine Listening in the Computer Science Program at the CUNY Graduate Center


The Computer Science PhD program at the CUNY Graduate Center and the department of Computer and Information Science at Brooklyn College are recruiting a PhD student in the area of Machine Listening. The successful candidate will apply and develop Machine Listening approaches to the analysis of 100,000 hours of acoustic recordings made at 100 sites in Northern Alaska and Yukon Territory over 5 years. The student will utilize human computation methods to train models that will be used to assess the effects of human-generated and environmental factors on the behavior and distribution of songbirds, waterfowl, caribou, and other wildlife.

Four years of stipend (~$29,000), tuition waivers, and health insurance are provided through an award from the National Science Foundation. This research will be carried out in collaboration with investigators from Columbia University, University of Alaska Fairbanks, and Colorado State University. The successful candidate may also work closely with state, federal, and provincial agencies, along with Alaska Native and Canadian First Nation organizations.


* Previous research experience in machine learning, especially as applied to audio. Preference will be given to applicants with peer reviewed publications at reputable venues in these areas.
* Exceptional organizational, time management, software engineering, and communication skills.
* Minimum undergraduate GPA>3.0, graduate GPA>3.5, GRE quantitative score >70 percentile, GRE verbal score >50 percentile

To apply:

Applications to the PhD program are due by January 8, 2019 and are made online at:

More information about the PhD program is available at its website:

For more details on the position, please email Prof. Mandel at . Applications are particularly encouraged from members of communities traditionally underrepresented in computer science.


Apply Now