PhD on mixed-signal spiking neural networks for bioinspired artificial olfaction

PhD on mixed-signal spiking neural networks for bioinspired artificial olfaction

Published Deadline Location
29 Feb 12 Apr Eindhoven

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Job description

We aim to replicate traits of biological olfaction by combining mixed-signal Very Large Scale Implementation (VLSI) of massively parallel and ultra-low-power spiking neural networks with synthetic biological components. Our research aims to establish an integrated platform for chemical sensing, enabling the exploration and understanding of biological olfaction's sensing and computing aspects.

Job Description

In the human brain, sensory neurons relay crucial information about our surroundings, including light, touch, sounds, taste, and smell. Through the cutting-edge fields of neuromorphic computing and synthetic biology, we aim to endow artificial systems with a highly accurate, robust, and efficient capability for detecting scents, or olfaction.

Biological systems' ability to smell surpasses conventional chemical detection methods in several key aspects, including sensitivity, specificity, reaction times, encoding capacity, durability, compactness, and energy efficiency. This superior performance is largely attributed to the sophisticated design of the olfactory system, which has been refined through millions of years of evolution across all living creatures, from the smallest insects to the largest mammals. These biological systems rely on membrane proteins equipped with specialised channels that can identify specific odour molecules, leveraging an incredibly effective and flexible computing platform provided by spiking neural networks.

Thus, the main broad research questions are:

'How can we engineer advanced spiking neural networks and leverage VLSI (Very Large Scale Integration) technologies to mirror the complex structure of the biological olfactory system in artificial devices? By focusing on the integration of membrane proteins with specialised channels and incorporating cutting-edge spiking neural networks capable of online learning, we aim to achieve a precise, adaptable, and efficient artificial olfactory system for recognizing odour molecules'

To answer these questions, we seek highly motivated, self-driven Ph.D. research that will contribute to the SYNCH project 'Combining SYnthetic Biology & Neuromorphic Computing for CHemosensory perception'. SYNCH will be conducted in the Neuromorphic Edge Computing Systems Lab, within the Electronic Systems Group (ES) at TU/e. The SYNCH project is a collaborative endeavour involving CAU Kiel University in Germany and the University of Bern in Switzerland.

The Ph.D. research will focus on exploring new neuromorphic microelectronic circuits in VLSI technology, and we will closely collaborate  with synthetic biological experts. The research will delve into crucial aspects of computational properties in biological neural systems and the final goal is to create a unified chemical sensing platform by combining neuromorphic electronic systems with synthetic biological mediums—a pioneering endeavour.


Eindhoven University of Technology (TU/e)


  • A master's degree (or an equivalent university degree) in Electrical Engineering, Biomedical Engineering, or related background and strong hardware design skills.
  • Has a background in analog mixed-signal designs, devices and general knowledge of semiconductor physics, modelling, and electronic system design.
  • Has knowledge of circuit simulation and VLSI design (spice, cadence, synopsys tools).
  • A research-oriented attitude, is capable of taking initiative, and has a strong problem-solving attitude.
  • Ability to work in an interdisciplinary team.   
  • Motivated to develop your teaching skills and coach students.
  • Fluent in spoken and written English (C1 level).      

Conditions of employment

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.


  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V36.7303


Eindhoven University of Technology (TU/e)

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De Rondom 70, 5612 AP, Eindhoven

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