At the Intelligent Microsystems Lab, our research traverses various levels of abstraction including systems, circuits, and algorithm design residing at the interface of machine intelligence and cyber-physical systems. We study neuromorphic and other non-von Neumann architectures where we leverage energy efficiencies in analog-CMOS and alternative (Beyond CMOS) computing structures to deliver orders of magnitude improvement in the performance of adaptive and learning systems. We work closely with groups developing new devices and materials to help us develop new chips aimed at achieving the limits of energy efficiency.
Openings for PhD students
We are actively looking for motivated students who are interested in pursuing Ph.D. degrees in the topic of exploring algorithms, architectures, or circuit-level techniques to develop energy-efficient intelligent systems.
In particular, we are looking for self-motivated PhD students with the following backgrounds:
Hardware design for machine learning and deep neural networks, and experiences with reinforcement learning, generative models, and strong coding (C++ and Python) and experiences with deep learning platforms such as PyTorch or Tensorflow will be a big plus.
VLSI circuit design and computer architecture, and CMOS chip tape-out and testing experiences will be a big plus.
How to apply
If you are a prospective student interested in the PhD program at Notre Dame, please send me an email containing with your CV and some details on what aspect of our research interest you. You may apply to either the Electrical Engineering department or Computer Science and Engineering department online (deadline December 15 for fall enrollment).
Openings for Postdoctoral Scholars
There is an opening for a post-doc on VLSI and analog-computing DNN accelerators. (requirement: successful digital or analog chip tape out experience). Senior IC designers are expected to implement novel circuit blocks for neural interfaces, such as low-noise amplifiers and specialized machine learning hardware in Cadence. Applicants with strong background in analog/digital and mixed-signal integrated circuits are encouraged to apply.
Postdoctoral candidates are expected to have a PhD in Electrical Engineering, Computer Science, or a related field with a proven track record of conducting high quality research. Appointments are for a period of one year, but our expectation is that it would be renewed, assuming satisfactory research progress.
How to apply
If you are a postdoc candidate, please send me an email containing your CV, research statement, and two names for requesting reference letters.