PhD - Leuven | More than two weeks ago
Thanks to the artificial intelligence revolution, digital photography witnesses a paradigm shift from simply taking pictures to sensing specific information. Among those sensing applications, TOF has been most successful by being adopted in the consumer electronics widely. However, its usage is limited to short distance detection because of the insufficient performance in the longer range. Active illumination in SWIR (short-wave infrared, with wavelength above 1.4 um) has advantage over NIR (near infrared, with most used wavelengths below 1 um) due to less ambient light and better eye safety, eventually can be used to achieve longer working distance TOF. Based on our strong expertise in designing with and processing foreign materials which can effectively detect SWIR, strives to be at the forefront these new developments.
The goal of this PhD is to develop SWIR TOF image sensor technology. This research starts from material and device structure understanding via literature studying and TCAD simulation. Actual design/layout of the SWIR TOF image sensor using novel device structure and state of the art processing follows. Eventually, evaluation and analysis in different perspectives with a technology demonstration will be key.
You are a highly motivated recent graduate holding a degree in nano-engineering, physics, material science, electrical engineering, or related. You have a strong knowledge on solid state device physics and basic circuit design capability plus interest in digital photography. You are a team player and have good communication skills as you will work in a multidisciplinary and multicultural team spanning several departments. Given the international character of , an excellent knowledge of English is a must.
Required background: nano-engineering, physics, materials science or electrical engineering with strong affinity for device physics
Type of work: 10% literature study, 20% simulation, 40% design, 30% characterization
Supervisor: Paul Heremans
Daily advisor: Jiwon Lee, Pawel Malinowski
The reference code for this position is 2021-105. Mention this reference code on your application form.