Monday, December 6th, 2021

Call for Applications: Participants in Research Pods in Quantum Computing and Machine Learning

The Simons Institute’s Research Pod in Quantum Computing and Research Pod in Machine Learning invite applications for postdoctoral fellows for the 2022–23 academic year. The Quantum Pod is also accepting applications for visiting research scientist positions.

Quantum Pod Opportunities
In the wake of the National Quantum Initiative, the Simons Institute’s Research Pod in Quantum Computing brings together researchers from computer science, physics, chemistry, and mathematics to study pressing issues in quantum algorithms, complexity theory, error correction, and near-term quantum devices. This research pod facilitates deep interactions between quantum computing and the rest of theoretical computer science and will help introduce and welcome the larger TCS community into quantum computing research issues. This initiative is led by Simons Institute Research Director for Quantum Computing Umesh Vazirani and is supported in part by the Department of Energy, via the newly established Quantum Systems Accelerator (QSA), and by the National Science Foundation, via the Quantum Leap Challenge Institutes (QLCI) award. 

How to apply to join the Quantum Pod: Interested candidates should follow the instructions for the call for applications for postdoctoral researchers or visiting research scientists. Applications will be considered on a rolling basis. The first review date for postdoctoral fellows is December 15, 2021.

 

Machine Learning Pod Opportunities
The Research Pod in Machine Learning brings together researchers from theoretical computer science, mathematics, statistics, electrical engineering, and economics to develop the theoretical foundations of machine learning and data science. Led by Simons Institute Associate Director Peter Bartlett, this pod is partially funded by a $12.5 million award made under the National Science Foundation's program on Transdisciplinary Research in Principles of Data Science to establish the Foundations of Data Science Institute (FODSI). This institute, a collaboration between UC Berkeley and MIT, partnering with Boston, Northeastern, Harvard, and Howard universities, as well as Bryn Mawr College, aims to improve our understanding of critical issues in data science, including modeling, statistical inference, computational efficiency, and societal impacts. The NSF, together with the Simons Foundation, is also supporting the activities of the pod through the Collaboration on the Theoretical Foundations of Deep Learning. This is a collaboration of 11 PIs from eight institutions around the world that aims to understand the mathematical mechanisms that underpin the practical success of deep learning. The Simons Institute will act as the convening center for many of these activities, hosting public events such as summer schools, research workshops, and other collaborative research opportunities.

How to apply for a postdoctoral fellowship in the Machine Learning Pod: Interested candidates should follow the instructions for the call for applications for postdoctoral researchers here and here. Applications will be considered on a rolling basis.