Postdoc position - Quantum materials & information at Brown’s new Theoretical Physics Center

The Brown University NSF EPSCOR Center focused on Harnessing the Data Revolution for the Quantum Leap: From Quantum Control to Quantum Materials seeks a highly talented and motivated postdoctoral fellow interested in working at the interface of quantum matter theory, quantum information, and machine learning. The fellow will help lead Center efforts and define the Center’s vision to develop new theories that leverage machine learning and quantum control to accelerate materials discovery. The fellow will therefore be engaged in multi-group collaborative research with other theorists and experimentalists at Brown, Dartmouth, and the University of New Hampshire, and will be expected to help train graduate and undergraduate students. The position represents an excellent opportunity to develop professional networks and enhance communications skills.

 

The fellow will become a member of Brown’s new Center for Theoretical Physics, which is comprised of a number of highly-regarded theorists from Brown’s physics, chemistry, environmental science, and applied mathematics communities. Brown University is a private, Ivy League University located in Providence, RI, less than an hour away from Boston and less than four hours away from New York City. The University is home to a lively campus, where students are intellectually engaged both inside and outside the classroom. Brown boasts a number of top-ranked Departments and is an institution at which interdisciplinary research is strongly embraced.

Ideal candidates should have a background in quantum condensed matter physics, familiarity with machine learning, and, at a minimum, an appreciation of quantum information science. An ability to work well with others is a must. Candidates with a demonstrated record of creativity and independent thought are preferred. Applicants from diverse backgrounds are strongly encouraged to apply. All hires will also be given time to explore research topics, continue past research, and develop collaborations of their own.

 

Those interested in applying should submit their cover letter, CV, and three recommendation letters through Interfolio (<https://apply.interfolio.com/68383>) by November 1, 2019 for full consideration.  The position is expected to begin by January 1, 2020 but there is some flexibility regarding the start date.