PHD Position Self Lab

Challenge Energy efficient and accurate hardware design for smart edge applications.
Challenge Develop new bio-inspired Machine learning algorithms
Challenge Develop mapping and programming models for neuromorphic hardware
Impact Healthcare applications such as medical implants that have significant societal impact.

TU Delft is a top tier university and is exceedingly active in the field of Artificial intelligence.

SELF targets the design and development of smart edge computing engines, and demonstrating their superiority for personalize healthcare such as epilepsy early detection; epilepsy is a neurological disease that manifests as a brain-wide phenomenon. The computing engine will be based on computation-in-memory architecture (going beyond traditional Von-Neumann) making use of memristor devices (being very suitable for brain inspired computing), combined with new biological inspired learning algorithms and power-aware efficient mapping methods. In order to:

• develop software-based energy-efficient framework for mapping Spiking Neural Network (SNN) application to neuromorphic hardware.
• develop software libraries to reduce the size of the network without impacting its overall accuracy as well as
• develop software models for processing streaming data with low-latency SNNs on low-power Edge devices, using insights from the latest ML-oriented bi-level optimization tools

Daily supervisor EWI/ST: Luis Cruz. Daily supervisor EWI/DIAM: name will be announced later.

Position -1: To develop an SNN based ASIC for massively parallel neural interfaces with active digital pixels for amplification, filtering and digitization of the neural signals. Moreover, investigate compression and/or feature extraction at the sensor location for reducing the data movement cost from the sensors to the Spiking Neural Network engine.

Position-2: To develop software-based energy-efficient framework for mapping Spiking Neural Network (SNN) application to neuromorphic hardware. Furthermore, to develop software libraries to reduce the size of the network without impacting its overall accuracy as well as software models for processing streaming data with low-latency SNNs on low-power Edge devices, using insights from the latest ML-oriented bi-level optimization tools.

We expect you to have:

• Completed a relevant MSc degree in Electrical Engineering or Computer Science or any other related field relevant to PhD research;
• An affinity with teaching and guiding students;
• Proficiency in expressing yourself verbally and in writing in English;
• The ability to work in a team and take initiative.
• Good understanding of machine learning algorithms, software programming and mathematical optimization methods (continuous and/or discrete).

Additionally, in order to be successful, there are some extra requirements per position:

Position -1: you should have good understanding of HDL language, ASIC flow, micro-architecture, digital design and familiarity of tape-out process.

Position -2: you should have a good understanding of machine learning algorithms, software programming and mathematical optimization methods (continuous and/or discrete).

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements .

You will be offered a 5-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 3,5 years assuming everything goes well and performance requirements are met.

You will be deployed for AI-related education for the usual teaching effort for PhD candidates in the faculty plus an additional 20%. The extra year compared to the usual 4-year contract accommodates the 20% additional AI, Data and Digitalisation education related activities. All team members have many opportunities for self-development. You will be a member of the thriving TU Delft AI Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

For information, please contact: Dr. ing. Rajendra Bishnoi,[email protected].

Are you interested in this vacancy? Please apply no later than February 4, 2024 via the
application button.

Please submit the following:

• 1-page Motivation letter
• Your CV
• (part of your) M.Sc. thesis or a paper that you have written, in which you
  demonstrate your writing (and scientific) skills

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post.

Please do not contact us for unsolicited services.