1 Mar 2024
Job Information
- Organisation/Company
Eindhoven University of Technology (TU/e)- Research Field
Technology- Researcher Profile
First Stage Researcher (R1)- Country
Netherlands- Application Deadline
12 Apr 2024 - 22:00 (UTC)- Type of Contract
Temporary- Job Status
Not Applicable- Hours Per Week
38.0- Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme- Is the Job related to staff position within a Research Infrastructure?
No
Offer 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.
Requirements
Specific Requirements
- 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).
Additional Information
Benefits
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.
Additional comments
About us
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
The Neuromorphic Edge Computing Systems Lab (NECS) is managed by Dr. Federico Corradi and is part of the Electronic Systems (ES) group (tue.nl/es). The ES group is a top research group consisting of five full professors, three associate professors, five assistant professors, several postdocs, about 40 EngD and PhD candidates, and support staff. The ES group is world-renowned for its design automation and embedded systems research. Our ambition is to provide a scientific basis for design trajectories of electronic systems, ranging from digital circuits to cyber-physical systems. The trajectories are constructive and lead to high-quality, cost-effective systems with predictable properties (functionality, timing, reliability, power dissipation, and cost). Design trajectories for applications that have strict real-time requirements and stringent power constraints are an explicit focus point of the group.
Curious to hear more about what it's like as a PhD candidate at TU/e? Please view the video.
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Federico Corradi, assistant professor, [email protected] .
Visit our website for more information about the application process or the conditions of employment . You can also contactLinda van den Boomen, HR advisor, [email protected] .
Are you inspired and would like to know more about working at TU/e? Please visit our career page .
Application
We invite you to submit a complete application by using the apply button.
The application should include a:
- Cover letter in which you describe your motivation and qualifications for the position.
- Curriculum vitae, including a list of your publications and the contact information of three references.
- Transcript of master's and bachelor's degrees.
- Copies of your final MSc thesis, including English abstracts, and (if applicable) published papers (PDF files). Submit at least one document written in English of which you are the main author.
- Results of your IELTS or TOEFL test (or equivalent).
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.
- Website for additional job details
https://www.academictransfer.com/338442/
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Eindhoven University of Technology (TU/e)
- Country
- Netherlands
- City
- Eindhoven
- Postal Code
- 5612 AP
- Street
- De Rondom 70
- Geofield
Where to apply
- Website
https://www.academictransfer.com/en/338442/phd-on-mixed-signal-spiking-neural-n…
Contact
- City
Eindhoven- Website
http://www.tue.nl/- Street
De Rondom 70- Postal Code
5612 AP
STATUS: EXPIRED
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