Our research group has three openings for self-motivated Ph.D. students in the following areas. If you are interested, please email your CV, transcript and research interests.
01
Developing ML-based EDA tools
The position will involve:
- Machine learning models for physical design problems (timing analysis, power, thermal, place and route)
- ML-EDA research infrastructure and open-source development
- Large-language models to assist chip design
- Reinforcement learning algorithms for chip design
Minimum qualifications:
- Strong Python and C/C++ programming
- Motivation to read research papers to understand state-of-the-art algorithms in EDA
- Basic knowledge of the VLSI design flow
- Basic knowledge of machine learning
02
Developing EDA Tools to Enable Heterogenous Integration (HI)
The position will involve:
- Electronic design automation (EDA) algorithms for the design of HI-based (2.5D and 3D) systems
- EDA tools for SoC disaggregation and pathfinding
- EDA tools for thermal and power analysis of 2.5D and 3D architectures
Minimum qualifications:
- Strong C/C++ programming skills
- Motivation to read research papers to understand state-of-the-art models and challenges
- Basic knowledge of algorithms and data structure
- Basic knowledge of VLSI design using chiplets
03
Developing EDA Tools for Environmentally Sustainable Computing
The position will involve:
- Models to estimate carbon footprint for different design technologies
- Electronic design automation (EDA) algorithms that analyze and optimize large-scale systems for carbon footprint
- Sustainability-centric design techniques for VLSI systems
Minimum qualifications:
- Strong Python programming
- Motivation to read research papers to understand state-of-the-art models in designing chips for environmental sustainability
- Basic knowledge of the VLSI design flow