Phd Position In CMOS Design Of Ssm - based Spiking Neural Networks Integrated With Risc - v

PhD Position In CMOS Implementation Of State-Space Model-driven Spiking Neural Networks

The Institute of Mechanical and Electrical Engineering at SDU invites applications for a 3-year PhD position focusing on CMOS implementation of State-Space Model-driven Spiking Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing.

The research aims to develop ultra-low-power computing chips that support spike-based processing and memory-efficient computation using SSMs, targeting edge-AI scenarios in wearables, robotics, or sensor networks.

The project will co-design SSM-inspired spiking neural network (SNN) cores and integrate them with a low-power RISC-V processor. The PhD candidate will develop spike-based computing blocks and explore hybrid analog/digital CMOS implementation of event-based processing for edge-AI applications.

The project will explore:

• SSM formulations adapted to spiking dynamics
• SSM implementation for time-series classification applications
• Co-integration of SSM-SNN cores with RISC-V processors in CMOS
• Hybrid analog/digital interfaces for spike generation and propagation
• Event-based communication protocols for ultra-low-power operation
• Hardware-software co-simulation and benchmarking

This PhD project is part of SDU microelectronic unit's effort in neuromorphic chip design and collaborates with international partners working on spiking AI and custom processors.

Work description:

• Investigate SSM representations compatible with spiking dynamics
• Investigate the usage of SSM along with sensor devices.
• Design digital/analog building blocks for SSM-SNN cores
• Integrate RISC-V processors using SoC flows
• Perform full-chip simulation, verification, and prototyping
• Publish and present research in high-impact venues

Qualifications:

• Applicants must hold an MSc in electronics, computer engineering, or a closely related field.
• Strong background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles.
• Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre; Synopsys or Mentor Graphics.
• Strong programming skills: Python and C/C++.
• Experience in hardware accelerators, in-memory processing, or SoC integration.
• Strong analytical and problem-solving skills, with the ability to work independently and in collaboration with multidisciplinary teams.
• Excellent verbal and written communication skills in English.

Preferred qualifications:

• Hands-on experience with layout and tape-out of CMOS/VLSI chips.
• Strong background in VLSI digital design workflow, RISC-V architecture, and neuromorphic principles (Spiking neural networks).
• Experience in neuromorphic computing, in-memory processing, or SoC integration.

For further information, please contact Professor Farshad Moradi, moradi@sdu.dk.

If you experience technical problems, please contact hcm-support@sdu.dk.

Application procedure:

Before applying the candidates are advised to read the Faculty information for prospective PhD students and the SDU information on how to apply.

Assessment of the candidates is based on the application material, and an application must include:

• Motivated application.
• Curriculum Vitae.
• Master's and bachelor's degree certificates or equivalent, including transcripts of grades (copy of original/official English translation).
• Completed TEK PhD application form for 5+3 applicants. Find the form at the Faculty website.
• Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website.
• An official document describing the grading scheme of the awarding universities (if not Danish).
• Only for applicants from programmes that evaluate thesis/examination project by approved/not approved: An official written assessment of the thesis or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme.
• List of publications and maximum 2 examples of relevant publications (in case you have any publications).
• References may be included, you're welcome to use the form for reference letter at the Faculty website.
• A statement/documentation of other qualifications relevant to the position may also be included.

SUBMISSION GUIDE: Motivated application shall be uploaded as 'Cover letter' (max. 5 MB), Curriculum Vitae shall be uploaded as 'Resume' (max 5 MB). All other documents shall be uploaded as 'Miscellaneous documents' (max 10 files of max 50 MB per file).

The application deadline is September 15, 2025, at 11:59 PM / 23:59 (CET/CEST).

Applications will be assessed by an assessment committee. Shortlisting may be applied, and only shortlisted candidates will receive a written assessment. Interviews and tests may be part of the overall evaluation.

Appointment as a PhD fellow is a 3-year salaried position, and the monthly gross salary incl. pension is 36,138 DKK. If you have relevant postgraduate experience, you may be placed on a higher salary step.

The start date will be agreed with the successful candidate.

Applicants must hold a master's degree (equivalent to a Danish master's degree) at the time of enrollment and employment. Employment is contingent on enrollment approved by the PhD School. Enrollment will be in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order). Employment will be in accordance with the collective agreement between the Ministry of Finance and the Danish Confederation of Professional Associations for academics in the state with the associated circular on the job structure for academic staff at Danish universities and the provisions for PhD fellows as described herein as well as the Protocol on PhD fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations (AC). The person employed in the position may, based on a specific individual managerial evaluation, be exempted from time registration, also known as a 'self-organizer'.

The University of Southern Denmark wishes our staff to reflect the surrounding community and therefore encourages everyone, regardless of personal background, to apply for the position. SDU conducts research in critical technologies, which, due to the risk of unwanted knowledge transfer, are subject to a number of security measures. Therefore, based on information from open sources, background checks may be conducted on candidates for the position.