PhD in Digital Design of Oscillatory Neural Networks for Edge AI

Project

The research project is focused on investigating Oscillatory Neural Networks (ONNs) computing paradigm for edge AI applications and algorithms, including classification, sensor signal processing, decision-making, online learning, reinforcement learning, and more. ONNs constitute a novel class of neural networks where information is encoded through the phase difference among oscillators. They exhibit promising characteristics for associative memory tasks, and the goal is to delve deeper into their computational properties for real-world applications in edge AI.

Candidate

We are seeking a motivated PhD candidate to join our team working on cutting-edge research and development in the field of AI/ML based on Oscillatory Neural Networks (ONNs). The project aims to explore the potential of ONNs for various edge AI applications, including pattern recognition, signal processing, and real-time decision-making. As part of the project, you will be responsible for designing and implementing digital logic circuits and implementation on FPGAs to realize ONN architectures and algorithms.

• Design and implement digital logic circuits for ONN architectures using hardware description languages (Verilog/VHDL).
• Develop and optimize FPGA designs for efficient implementation of ONN algorithms for different AI/ML related applications.
• Develop multi-modal processing with ONN for image and sensor processing such as time series data. Develop demonstrators to showcase on real applications.
• Perform synthesis, place-and-route, and timing analysis to ensure FPGA designs meet performance, area, and power consumption requirements. Test and debug FPGA implementations using simulation tools and hardware testing platforms.
• Collaborate with interdisciplinary team members to integrate FPGA-based ONN solutions into larger systems.

Qualifications:

• Master's degree in electrical engineering, Computer Engineering, or related field.
• Proven experience in digital logic design and FPGA implementation, preferably in the context of neural networks.
• Proficiency in hardware description languages (Verilog/VHDL) and FPGA design tools (Xilinx Vivado).
• Strong understanding of digital signal processing, synchronous/asynchronous design techniques, and FPGA architecture.
• Excellent spoken and written English skills.

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.