The Neuromorphic Edge Computing Systems (NECS) Lab at the Eindhoven University of Technology invites applications for one Ph.D. position from a passionate and innovative young researcher. Our mission is to overstep the boundaries of artificial intelligence (AI) and neural networks, challenging the current computing paradigms by drawing inspiration from biological neural networks.

Despite significant advances in AI, current systems must catch up to the animal kingdom's efficiency in processing complex, real-time tasks with minimal energy in uncertain conditions. This limitation stems from a fundamental difference in design philosophy; while nature leverages distributed processing and inherent noise tolerance, modern computing relies on deterministic, bit-perfect operations with a clear separation between memory and computation. To bridge this gap, the NECS Lab is pioneering research into brain-inspired computing models that mimic the natural neural system's computational physics. Our research entails the development of novel brain-inspired computing theories, learning systems, and the design of ultra-low-power circuits, systems, and computing architectures.

We are seeking one PhD candidate interested in performing research in the following areas:

1. Ultra-low-power Mixed-signal Circuits and Architecture: Design of novel CMOS-based architectures for spiking neural networks that embody the brain's adaptive capabilities.
2. Spike-based Neuromorphic Hardware for Machine Intelligence: Embedding complex AI functionalities into heterogeneous neuromorphic hardware that integrates emerging technologies (e.g., ReRAM, Phase-Change Memories) with traditional CMOS for increasing the energy efficiency of embedded devices.

With these research focus, the NECS lab aims to push the boundaries of energy efficiency and integration of AI-capabilities in embedded devices, paving the way for a new generation of neuro-inspired processors for efficient autonomous agents.

Job Description

We offer an exciting Ph.D. opportunity for a pioneering approach to neuromorphic engineering and computing, drawing inspiration from neural mechanisms observed in biological neural systems.

Key responsibilities:

1. Engage in groundbreaking research to develop advanced neuromorphic sensing, and computing systems by taking inspiration from the sensing and computing capabilities of natural neural systems.
2. Innovate in the areas of signal encoding, processing pipelines, and embedded computer architectures to emulate bio-inspired computational models effectively.
3. Explore and implement beyond traditional deep learning techniques, moving towards the next generation of neuromorphic technologies. This includes leveraging spiking neural networks' efficiency, parallelism, and adaptability for enhanced sensing and computing.
4. Delve into new bio-inspired theories and connect them to hardware architectures.

• A master's degree (or an equivalent university degree) in Electrical Engineering, Computer Science, Physics, or related fields, with an interest in neuromorphic computing and engineering.
• Has a strong background in one or more of the following:
• Analog mixed-signal designs, devices, and general knowledge of semiconductor physics. modeling, and electronic system design.
• Knows circuit simulation and VLSI design (spice, cadence, Synopsys tools).
• Experience with hardware architecture, FPGA, and system-level simulation is desirable.
• A good theoretical understanding of statistics and machine learning theory.

• Strong analytical skills and proficiency in programming and simulation tools.
• Ability to work independently and collaboratively in a multidisciplinary team.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

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. €2,872 max. €3,670).
• 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.