SUTD was established in 2009 as a collaboration with MIT, and has recently in 2018 topped the list of emerging engineering schools in the world. At SUTD, there is a strong emphasis on interdisciplinary and collaborative research. Our unconventional naming of departments (or pillars) is a reflection of our philosophy that impactful research would naturally encompass multiple disciplines. SUTD is located in Singapore, a multiracial multicultural country, where English is the main language used in all schools and most workplaces, especially among people of different races. We are seeking a highly motivated research fellow with strong algebraic background, who is interested to explore new research directions in deep learning, and more generally in Artificial Intelligence. The successful candidate can expect to conduct research on a completely new topic that combines commutative algebra with AI, and will work closely with other team members. The goal of this project is to develop an algebraic framework for understanding the architecture hyperparameters of deep neural networks, especially in relation to unsupervised feature learning. This framework shall be based on methods from both commutative algebra and computational algebra. We shall also build upon this algebraic framework and develop algorithms for generating optimal neural network architectures that are able to perform optimized feature learning on unlabeled data sets. Duration of position: 2 years. (One post-doctoral position available)
Interested candidates should submit a current CV and copies of academic transcripts (from both undergraduate and post-graduate studies), as well as arrange for one reference letter. The candidate should ideally start as soon as possible, but the starting date is negotiable. Any queries can be sent directly to Ernest Chong (ernest_chong@sutd.edu.sg) with the email subject header "AI Research Fellow position for project on algebraic framework". |