PhD Fellowship

About the Fellowship

This is a unique opportunity to lead research on physics-informed neural networks. You will work alongside our team as a member of technical staff during the fellowship to conduct research, exploring challenging scientific questions, and help inform our approach to advancing the field of electronics.

Who this is for

If you are currently pursuing or recently earned a PhD in Math, Physics, Electrical Engineering, or Machine Learning this Fellowship is for you. The fellowship is on-site only in NYC. Fellows are encouraged to go full-time with us during the fall 2026 season but we are open to discussing part-time depending on your needs.

What you will do

• Work alongside the team to develop new approaches to artificial intelligence in the field of electronics.
• Design experiments and benchmarking methodologies.
• Develop novel machine learning architectures.
• Create differentiable simulation pipelines.
• Design new electronics and collect test measurements.
• Build large-scale datasets for scientific reasoning.
• Investigate new approaches to representation learning for engineering.
• Conduct literature reviews and propose original research directions.
• Train and evaluate research models.
• Publish internal research reports and, where appropriate, academic papers.