Student project at imec (Thesis)
In this project, the student will research and develop innovative ultra-low power (ULP) circuit to interface with an ultrasound transducer array for 3D ultrasound imaging.
What will you be doing?
The use of ultrasound imaging is widespread and in the past few years there has been a growing interest in closely coupling the transducer array closely with the control and readout transceiver circuits. We envision that in the next-generation ultrasound imaging platforms, the transducers, readout electronics and intelligent inference will come together on a single platform. This technology can allow very low-cost ultrasound imaging for point-of-care or in-home use. In this project, you will be in the pole position to make this vision into reality.
You will survey the state-of-the-art for 3D ultrasound sensor systems and circuits including methods used for beamforming. Based on this study and in collaboration with IMEC experts on PMUT transducer arrays and signal processing, you will research and develop ultra-low-power system and circuits for ultrasound imaging. You will have the opportunity to tape-out and validate your designs in silicon. You may also collaborate with IMEC experts in neuromorphic circuits, also phase array beamforming to explore techniques to closely couple the transducer interface circuits with neural networks for on-chip inference.
Some relevant papers are:
E. Kang et al., "A Variable-Gain Low-Noise Transimpedance Amplifier for Miniature Ultrasound Probes," in IEEE Journal of Solid-State Circuits, vol. 55, no. 12, pp. 3157-3168, Dec. 2020, doi: 10.1109/JSSC.2020.3023618.
J. Lee et al., " A 5.37mW/Channel Pitch-Matched Ultrasound ASIC with Dynamic-Bit-Shared SAR ADC and 13.2V Charge-Recycling TX in Standard CMOS for Intracardiac Echocardiography," 2019 IEEE International Solid- State Circuits Conference - (ISSCC), San Francisco, CA, USA, 2019, pp. 190-192, doi: 10.1109/ISSCC.2019.8662531.
C. Chen et al., "A 0.91mW/element pitch-matched front-end ASIC with integrated subarray beamforming ADC for miniature 3D ultrasound probes," 2018 IEEE International Solid - State Circuits Conference - (ISSCC), San Francisco, CA, 2018, pp. 186-188, doi: 10.1109/ISSCC.2018.8310246.
M. Chen et al., "27.5 A pixel-pitch-matched ultrasound receiver for 3D photoacoustic imaging with integrated delta-sigma beamformer in 28nm UTBB FDSOI," 2017 IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, CA, 2017, pp. 456-457, doi: 10.1109/ISSCC.2017.7870458.
Your Tasks Involve:
Literature survey the state-of-the-art for ultrasound transducer interface front-end circuits.
Research and development of an architecture and circuits for low-power mixed-signal front-end receiver/transmitter to enable 3D ultrasound imaging.
Collaborate with IMEC experts in ultrasound transducers, mixed-signal circuits and signal processing algorithms to maximize your research impact.
Modelling of the system in MATLAB or Python.
Development of integrated circuits for the front-end electronics including drawing the schematic and layout using Cadence EDA tools.
Tape-out and measurement of the chip (if time permits).
Optionally, analysis and development of appropriate inference techniques using on-chip neural networks.
What we do for you
You will be working on cutting-edge research on a topic that is very relevant to both academic and industrial research groups. To help you in this journey, we offer a flexible environment where you can be the leader of your own research while at the same time have support of experts to complete your tasks. As part of the team in IMEC-Netherlands you will have opportunities to learn from the some of the best minds in analog, digital circuits as well as neuromorphic machine learning research.
IMEC has in-house experts in ultrasound transducers (PMUTs), mixed-signal circuit design as well as signal processing algorithms who can help you in shaping this multi-disciplinary research project.
Who you are
You are a Msc/Bsc student in Electronics Engineering.
You are available for a period of 12 months.
You have knowledge of analog/mixed-signal circuits through course and/or project work.
You are excited about low-power analog circuit design.
You are interested in AI, machine learning and neuromorphic circuits.
You have a background in analog/digital signal processing.
You are familiar with Cadence design environment or similar CAD tools.
You are familiar with MATLAB or Python.
You are entitled to do an internship in the Netherlands.
You are self-starter and able to work independently.
Good written and verbal English skills.
Click on 'apply' to submit your application. You will then be redirected to e-recruiting.
Please be advised that non-EU/EEA country students that are studying outside of the Netherlands, need to have a work-permit to be able to do an internship in the Netherlands.