Machine Learning for Integrated Circuit Design

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch

Job Description

Position Overview:

Are you interested in learning more about applying machine learning to solve real world problems? Our team consists of a group of domain experts in designing industry-leading high-speed wireline interfaces. We are exploring the exciting possibilities from advancement in machine learning and looking at how it can be leveraged to assist expert integrated circuit (IC) designers. This is an uncharted territory awaiting a self-motivated and curious individual to take on the challenge which combines the well-established electronics field with the potential of artificial intelligence. You will design experiments, invent new algorithms, and create prototype implementations focusing on solving the unique problems in circuit design. Some knowledge in integrated circuit design and machine learning will be helpful. You will be working within a highly research orientated team composed primarily of recent U of T graduates and professors.

Responsibilities:

• Perform state-of-art research survey for related work
• Help develop methodologies for quantifying and comparing performance across different machine learning algorithms
• Experiment with different algorithms to train models for circuit design optimization problems
• Conduct sensitivity analysis on different algorithms clearly highlighting their impact on the overall system performance
• Clearly documenting experiment results and making sure of its repeatability

Qualifications

• Finishing 3rd year undergraduate studies in ECE or Computer Science specializing in machine learning
• At least 1+ year of experience working in the field of machine learning would be preferred
• Skills with programming language like MATLAB, Python or similar scripting language.
• Understanding of fundamental machine learning concepts
• Experience with one or more mainstream deep learning frameworks such as TensorFlow, PyTorch and Keras is an asset.
• Understanding of circuit design is a plus
• Experience working with open source libraries is a plus
• Proven team player with strong communication skills.