What you will do. Artificial Intelligence (AI) starts to be embedded everywhere around us (phones, wearables, cars, etc.). Computing the AI models presents new challenges for processors: a massively parallel computation of millions of artificial neurons in almost real time. For that, new processor architectures have the potential to increase the energy-efficiency of AI computation by several orders of magnitude. They rely on new computing principles, such as analog computing and compute-in-memory (CIM) and new memory devices called emerging Non-Volatile Memories (eNVMs). There are multiple candidate technologies to enable the power of eNVMs, such as Resistive RAMs, magnetic RAMs or Ferroelectric components. However, these analog computing principles and emerging devices introduces variability and reliability issues for CIM processors. Hence, it is necessary to tackle these issues to enable a true development of such computing technologies in the future. In this doctoral thesis topic, you will be working in a major European project developing self-calibration and self-adaptation methodologies for analog CIM chips based on eNVMs. Your design will be integrated with state-of-the-art CIM macros and you will have the opportunity to be among the first to access these eNVM technologies.
What we offer you.
(1) An exciting working topic. You will develop competences at the interface between IC design and eNVMs. You will think about research solutions for emerging technologies
(emerging memories and CIM);
(2) The use of cutting-edge IC design tools. You will design ICs in the latest nanometer-scale CMOS technologies, participate in multi-project wafer runs annually and use a
state-of-the-art measurement lab.
(3) A supportive working environment. You will integrate an international and supportive research team working with international partners. You will be in touch with a vast network of
academic and industrial partners, living in Belgium, at the heart of innovation in IC design and AI in Europe.
Who you are.
- You have a master’s degree in electrical engineering. High average grades as well as excellent grades on courses on electronics are a clear asset.
- You just obtained your degree, or you already gained some industry experience.
- You are passionate about IC design and AI, you want to work on a multi-disciplinary topic.
- You have some hands-on experience or courses taken on IC design and tools (in particular Cadence). Specifically, experience and/or interests in analog/mixed-signal ICs are an asset.
- You are open-minded for new research, eager to learn more and fit to teamwork.
- You are fluent in English, and possibly in French.
More information? Do not hesitate to contact me via Email (available in this website)
Ready to apply?
Please submit your application by Email, martin.andraud(at)uclouvain.be. Please include the following documents in English (or French):
- Application letter (1 to 2 A4 pages)
- Course transcripts of Master studies with grades and Certificate of Master degree
- Curriculum Vitae (including list of publications if any, 1 to 2 A4 pages)
- Brief description of your research interests and what you want to do (0.5 to 1 A4 page)
- Possible References (names of referees or recommendation letters)