Doctoral Researcher in hardware-aware AI and analog/RF circuits

At Aalto University, science and art meet technology and business. We build a sustainable future by achieving breakthroughs in our key areas and at their intersections. At the same time, we inspire the changemakers of the future and create solutions to the world's great challenges. Our university community includes 16,000 students, 446 professors, and over 5,000 employees, representing a total of over 120 nationalities. Our campus is located in Espoo, Otaniemi. Diversity is part of us, and we work continuously to ensure the diversity and non-discrimination of our community. Therefore, we encourage qualified applicants from all backgrounds to join our community.

The Department of Electronics and Nanotechnology conducts research and organizes field-specific teaching in the areas of electromagnetics, micro- and nanotechnology, radio technology, and space technology. The department's research groups engage in active national and international cooperation with numerous research institutes and companies. The research groups have access to world-class research environments and equipment. The largest cleanrooms in the Nordic countries are located in the micro- and nanotechnology center, Micronova.

Doctoral Researcher in the field of hardware-aware AI and analog/RF circuits.

We are now looking for a doctoral researcher (PhD student) for the Tiny Systems and Circuits (TSirc) research group at Aalto University's Department of Electronics and Nanotechnology. In this position, you will build hardware-aware AI models for analog and RF circuits for 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 using Python
• You will validate the developed models against circuit simulations and measurements
• You will perform hardware-algorithm co-design for AI-driven 6G transmitters
• You will publish and present your results at leading international forums in the field and complete your doctoral thesis in Aalto University's Electrical Engineering doctoral program
• You will participate in teaching tasks as part of your doctoral studies

Your network and team Currently, our research group includes 1 professor, 4 doctoral students, and several master's and bachelor's level research assistants. The group is led by professor Kwantae Kim.

Your experience and goals We are looking for a proactive colleague. We expect from you:

• A Master's degree in electrical engineering, electronics, microelectronics, signal processing, or a suitable related field, as well as excellent academic performance. The degree must be completed by the start of the position.
• Practical experience in machine learning with Python, including training neural networks with PyTorch or a similar framework.
• Strong expertise in signals and systems as well as analog circuit theory.
• Strong logical thinking skills and good communication skills.
• English language skills sufficient for working. Proficiency in Finnish is not required.

The following will be considered an advantage:

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

What we offer

• You will have access to GPU computing for machine learning on Aalto's Triton computing cluster and established circuit simulation tools (Cadence, Synopsys, etc.) on the group's own computing cluster.
• In the School of Electrical Engineering, you will have access to RF measurement infrastructure with a frequency range extending from DC to the THz range.
• We collaborate with academic partners in Europe and Asia, including research visits abroad. This project has planned extensive collaboration with researchers from TU Delft, Yonsei University, and GIST.

The position is fixed-term and follows Aalto's established 2+2 model. The contract is initially for two (2) years, which includes a six (6) month probationary period. The contract is extended by two (2) years after a successful midterm review, making the total duration four (4) years. The starting salary for the doctoral researcher is approximately 3100 €/month.

Our primary workplace is located on the Otaniemi campus in Espoo. The position is full-time and requires presence on campus. Aalto University reserves the right to leave the position unfilled if no suitable applicant is found.

Interested? If you are interested, apply for the position by submitting your application through our recruitment system ("Apply now!" link) no later than 9.10.2026 (23:59 Finnish time). Incomplete applications (e.g., CV only) or applications sent via email will not be accepted. We encourage applying early, as we read applications as they arrive and may invite suitable candidates for an interview while the application period is still ongoing. All materials must be submitted in English as PDF files, a maximum of five (5) files, each no larger than 5MB. The application material must include:

• CV
• Motivation letter (maximum 1 page), in which you state:

* Why the research topic interests you * Why you want to join our specific group

• Transcript of records for Master's and Bachelor's degrees
• Letter of recommendation (maximum 1, if available), written recently for this application

The evaluation criteria for applications are described at https://kwantaekim.github.io/open-position/

Please note: Current employees of Aalto University must apply for the position through the internal Workday system (Internal Jobs) using their own Workday user ID, not through the external open jobs page. If you are an Aalto University student or visitor, apply with your personal email address (not aalto.fi) through the Aalto University open jobs page.

Want to know more? For more information about the open position, contact professor Kwantae Kim, kwantae.kim@aalto.fi. For questions regarding the recruitment process, contact HR Advisor, hr-elec@aalto.fi.

Read more about the TSirc research group: https://kwantaekim.github.io