Assistant Professor in Integrated Circuits Edge AI

Assistant Professor in Integrated Circuits for Edge AI

Personal type:
Scientific staff

Field of expertise:
Assistant Professor

Organisation:
Department of Electrical Engineering

Do you aspire to lead a research team, teach the next generation of engineers and are you ready to bridge the gap between innovative circuit design and practical edge AI applications?

The Department of Electrical Engineering , Integrated Circuits (IC) group is seeking an Assistant Professor in Integrated Circuits to strengthen our research and teaching in edge AI computing. We are looking for a researcher with expertise in energy-efficient analog and mixed-signal CMOS design, open-source chip design methodologies, and hardware accelerators for edge AI. This is a tenured position offering the opportunity to establish an independent, innovative research program while contributing to teaching and mentoring within the IC group and the EE department.

You will lead research on energy-efficient computing solutions such as neuromorphic, bio-inspired, and emerging computing paradigms for edge AI, with particular emphasis on in-sensor and near-sensor processing, low-power analog/digital/mixed-signal design, and open-source design tools and methodologies. The ideal candidate will combine deep expertise in circuit design with a commitment to accessible, reproducible research and a strong vision for advancing computing paradigms beyond conventional approaches.

Edge AI computing will enable the deployment of energy-efficient and scalable applications across smart systems, robotics, mobility, healthcare, high-tech systems, among others. You will secure competitive national and European funding and collaborate closely with industry and academic partners to develop transformative technologies for edge computing.

The Integrated Circuits group

This position is embedded in the Integrated Circuits group within the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). Our IC group consists of four full professors, four associate professors, five assistant professors, three support staff and many PhDs, Post Doc and EngD students. The IC group is world-renowned for its research on advanced integrated circuit design with a strong track record in analog and mixed-signal IC development.

The group has established expertise in RF/IF/LF circuit design for wireless application, sensor frontends, and computing systems with significant industrial partnerships. The IC group actively collaborates with university research centers and institutes especially the Casimir Institute . The IC group is a multi-cultural and diverse team.

This position represents an exciting opportunity to join IC group’s Nano Computing Research Lab and expand our growing research portfolio of novel computing paradigms for edge AI and neuromorphic computing. The successful candidate will strengthen the lab's capabilities in energy-efficient analog/mixed-signal design while establishing new research directions in open-source chip design methodologies, in-sensor processing, and hardware acceleration for edge AI. This growth will complement the group's existing research, industrial partnerships and create new synergies across the department, research centers and institutes.

Research Leadership

• Establish and lead an independent research program focused on energy-efficient CMOS design for edge AI, neuromorphic computing, and in-sensor/near-sensor computing.
• Develop domain-specific architecture and neuromorphic hardware accelerators for edge AI with emphasis on in-sensor/near-sensor processing architectures with direct sensor integration.
• Design and optimize RTL implementations and digital accelerator designs for neuromorphic and edge AI workloads, including mapping of algorithms to hardware.
• Conduct analog-digital co-design and mixed-signal SoC integration, combining custom analog signal conditioning with digital processing engines.
• Establish comprehensive design and validation flows encompassing layout and physical design, FPGA and ASIC prototyping, multi-project wafer (MPW) runs, and silicon measurement and characterization.
• Develop and promote open-source chip design methodologies and tools for accessible, reproducible research in integrated circuits.
• Supervise and mentor students, bachelors, masters, PhDs, Eng Ds and Post-Docs.
• Collaborate with faculty and experts across disciplines and industry.

Teaching & Curriculum

• Teach undergraduate and graduate courses in integrated circuits, digital design, analog circuits, or neuromorphic computing (as appropriate to departmental needs).
• Support existing curriculum and help develop innovative course(s) in emerging areas of circuit design and edge AI.
• Supervise PhD and Master's students in research and technical depth.
• Contribute and supervise to bachelor end projects and master graduation end projects.

Service & Professional Contributions

• Contribute to professional communities through conference organization, journal…