Doctoral Researcher in Hardware-Aware AI for Analog and RF Circuits

Aalto University; Espoo; On-site; EUR 31,000 - 38,000; Full time

Benefits offered by this job

GPU computing for ML

RF measurement infrastructure

Collaborations with international labs

Job summary

Aalto University in Espoo, Finland hires a Doctoral Researcher in Hardware-Aware AI for analog and RF circuits within the TSirc group. You will build hardware-aware AI models, validate them against circuit simulations and measurements, and contribute to hardware-algorithm co-design toward energy-efficient 6G transmitters.

The fixed-term four-year position starts with a salary around 3100 EUR per month and is on-site at Otaniemi.

Qualifications

• Hold a Master’s degree with an excellent academic record in Electrical Engineering, Electronics, Microelectronics, Signal Processing or related field.
• Practical experience in machine learning with Python, including training neural networks with PyTorch or similar framework.
• Solid background in signals and systems and analog circuit theory.
• Strong logical thinking and good communication skills; working proficiency in English.

Responsibilities

• Build hardware-aware behavioral models of analog and RF circuits in Python.
• Validate models against circuit simulations and measurements.
• Perform hardware-algorithm co-design for AI-driven 6G transmitters.
• Publish and present results at leading international venues and complete the doctoral thesis.
• Contribute to teaching duties as part of doctoral studies.

Skills

Machine learning with Python

Signals and systems

Analog circuit theory

English proficiency

Strong communication

Education

Master’s degree in Electrical Engineering or related field

Tools

Python

PyTorch

Cadence

Synopsys

Job description

Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges.Our community is made up of16000 studentsand 5 200 employees, including 446professors. Ourcampusisin Espoo, Greater Helsinki, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community

The Department of Electronics and Nanoengineering conducts research and arranges related courses in the fields of electromagnetics, micro and nanotechnology, radio engineering, and space technology. The department research groups have active national and international collaboration with several institutes and companies. Research groups are working with world-class research facilities and instruments; the largest clean rooms in the Nordic countries are located in the Micro- and nanotechnology centre Micronova.

Doctoral Researcher in Hardware-Aware AI for Analog and RF Circuits.

We are now looking for a Doctoral Researcher (PhD student) to join the Tiny Systems and Circuits (TSirc) group at Aalto University’s Department of Electronics and Nanoengineering. In this position you will build hardware-aware AI models for analog and RF circuits toward energy-efficient AI-driven 6G transmitters.

Your Role and Goals

As a Doctoral Researcher, you will:

• Build hardware-aware behavioral models of analog and RF circuits in Python
• Validate the developed models against circuit simulations and measurements
• Perform hardware-algorithm co-design for AI-driven 6G transmitters
• Publish and present your results at leading international venues, and complete your doctoral thesis in the Aalto Doctoral Programme in Electrical Engineering
• Contribute to teaching duties as part of your doctoral studies

Your Network and Team

Currently, our research group consists of 1 professor, 4 PhD students, and several MSc/BSc research assistants. The group is led by Professor Kwantae Kim.

Your Experience and Ambitions

We are looking for a self-motivated colleague who is expected to:

• Hold a Master’s degree, with an excellent study record, in Electrical Engineering, Electronics, Microelectronics, Signal Processing, or a closely related field, completed by the start of the position
• Have practical experience in machine learning with Python, including training neural networks in PyTorch or a similar framework
• Have a solid background in signals and systems as well as analog circuit theory
• Have strong logical thinking and good communication skills
• Have a working proficiency in English. (Finnish language is not required.)

The following are considered an advantage:

• Experience with laboratory measurements of analog or RF circuits
• Experience with signal processing for wireless communication
• Experience with transistor-level circuit design and simulation

What We Offer

• We provide GPU computing for machine learning on Aalto’s Triton high-performance computing cluster, alongside industry-standard circuit simulation tools (Cadence, Synopsys, etc.) on our own computing cluster.
• We provide RF measurement infrastructure covering DC to THz bandwidth at the School of Electrical Engineering.
• We collaborate with academic partners in Europe and Asia, including research visits abroad. In this project, extensive collaboration is planned with researchers from TU Delft, Yonsei University, and GIST.

The contract is fixed-term and follows Aalto’s standard 2+2 model. It will be made initially for two (2) years, with a six (6) month probationary period, and extended by two (2) further years after a successful mid-term review, giving a total duration of four (4) years. The starting salary for doctoral researcher is approximately 3100€/Month.

Our primary workplace is located at the Otaniemi Campus in Espoo, Finland. The position is full-time and on-site.

Aalto University reserve the right to leave the position unfilled if no suitable candidate is found.

Want to know more?

For more information regarding the open position, please contact Professor Kwantae Kim, [e-mail]. In any question regarding the recruitment process, please contact HR Advisor, [e-mail].