TheChallenge
Thin-film photodiode (TFPD) devices based on active materials,such as quantum dots, organic layers and perovskites, are constantly beingdeveloped and improved at imec to enable novel sensing capabilities beyondconventional silicon technology.
The active material properties are characterized by theprocess engineers who develop the photodiode structure in the lab and evaluatedevice performance on large, millimeter-sized single contacts. However, imagesensors contain hundreds of thousands of micrometer-scale pixels that operateunder conditions very different from laboratory test structures. As a result,processing-lab measurements do not translate directly to image sensors, wheredifferent properties matter and different characterization methods arerequired. Moreover, since the characterization can take a long time, it isimportant to automate the measurements where possible.
In this project we aim to expand the suite ofcharacterizations that are available to evaluate the performance of the imagesensors. We will develop procedures for image lag, blooming and MTF. Othermetrics could be included depending on the progress of the student.
What YouWill Do
Requirements
Time distribution
Type of internship: Master internship
Duration: 6-9 months
Required educational background: Electrotechnics/Electrical Engineering, Nanoscience & Nanotechnology
University promotor: Jan Genoe (KU Leuven)
Supervising scientist(s): For further information or for application, please contact Tristan Weydts (< E-Mail aus Sicherheitsgründen gelöscht >)
The reference code for this position is 2026-INT-220. Mention this reference code in your application.
Imec allowance will be provided for students studying at a non-Belgian university.
Applications should include the following information:
Incomplete applications will not be considered.
Thin-film photodiode (TFPD) devices based on active materials,such as quantum dots, organic layers and perovskites, are constantly beingdeveloped and improved at imec to enable novel sensing capabilities beyondconventional silicon technology.
The active material properties are characterized by theprocess engineers who develop the photodiode structure in the lab and evaluatedevice performance on large, millimeter-sized single contacts. However, imagesensors contain hundreds of thousands of micrometer-scale pixels that operateunder conditions very different from laboratory test structures. As a result,processing-lab measurements do not translate directly to image sensors, wheredifferent properties matter and different characterization methods arerequired. Moreover, since the characterization can take a long time, it isimportant to automate the measurements where possible.
In this project we aim to expand the suite ofcharacterizations that are available to evaluate the performance of the imagesensors. We will develop procedures for image lag, blooming and MTF. Othermetrics could be included depending on the progress of the student.
What YouWill Do
- Learn about the performance indicators of image sensors, including industry standards such as EMVA1288 and more custom methods.
- Implement measurement procedures, integrating the code into our existing measurement software written in Python.
- Write scripts and maintainable code to analyse the measurements and present the results in clear graphs and metrics.
- Develop the required hardware (PCB, mechanical, test setup) to perform the measurements in an automated manner.
- Apply the new methods to our library of image sensors with a wide range of materials, wavelengths and performances.
Requirements
- Programming knowledge, preferably Python
Time distribution
- 40% development, 40% lab, 10% literature study,10% reporting
Type of internship: Master internship
Duration: 6-9 months
Required educational background: Electrotechnics/Electrical Engineering, Nanoscience & Nanotechnology
University promotor: Jan Genoe (KU Leuven)
Supervising scientist(s): For further information or for application, please contact Tristan Weydts (< E-Mail aus Sicherheitsgründen gelöscht >)
The reference code for this position is 2026-INT-220. Mention this reference code in your application.
Imec allowance will be provided for students studying at a non-Belgian university.
Applications should include the following information:
- resume
- motivation
- current study
Incomplete applications will not be considered.
