Kwantae Kim
Just Landed
3 days ago
PhD in Hardware-Aware AI for Analog and RF Circuits at Aalto University Aalto University in Finland
Degree Level
PhD
Field of study
Computer Science
Funding
No explicit funding amount is stated. The post advertises a PhD position in the TSirc group and mentions access to a GPU computing cluster, circuit simulation tools, RF measurement infrastructure, and collaboration/possible research visits.
Deadline
Oct 9, 2026
Country
Finland
University
Aalto University
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About this position
PhD opening at Aalto University in the Tiny Systems and Circuits (TSirc) group for Hardware-Aware AI for Analog and RF Circuits.
This project sits at the intersection of Electrical Engineering and Computer Science, combining analog integrated circuits, RF circuits, neural network training, and PyTorch. The group highlights access to a GPU computing cluster (Aalto Triton), circuit simulation tools such as Cadence and Synopsys, and RF measurement infrastructure from DC to THz. The project also includes collaboration with TU Delft, Yonsei University, and GIST, with opportunities for research visits.
Eligibility highlights: practical experience training neural networks with PyTorch; strong background in signals and systems and analog circuit theory; fluent English. Helpful extras include lab measurements of analog/RF circuits, signal processing for wireless communication, and transistor-level circuit design and simulation. Finnish is not required.
Application deadline: 9 October 2026. The expected start date is Nov-Dec 2026.
How to apply: submit a CV, motivation letter, MSc/BSc transcript, and recommendation letter if available through the online application link. Email applications are not accepted, and early applications are encouraged because candidates may be reviewed and interviewed during the application period.
Funding details
No explicit funding amount is stated. The post advertises a PhD position in the TSirc group and mentions access to a GPU computing cluster, circuit simulation tools, RF measurement infrastructure, and collaboration/possible research visits.
What's required
Applicants should have practical experience training neural networks with PyTorch, a solid background in signals and systems and analog circuit theory, and fluency in English. Preferred pluses include lab measurements of analog/RF circuits, signal processing for wireless communication, and transistor-level circuit design and simulation. A MSc/BSc transcript, CV, motivation letter, and recommendation letter if available are requested.
How to apply
Prepare the required PDF materials: CV, motivation letter, MSc/BSc transcript, and recommendation letter if available. Submit the application through the linked online portal; email applications are not accepted. Apply early because candidates may be reviewed and interviewed during the application period.
More information can be found here
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