Coded Ptychography for Lens Free High Resolution Imaging Master internship - Leuven
Explore how smart optical encoding and algorithms can unlock a new generation of lens-free microscopes.
Lens-free imaging has emerged as a promising alternative to traditional microscopy, offering compact hardware, large field-of-view, and substantial cost and form-factor reductions. In coded ptychography, a patterned layer positioned near the sensor introduces spatial modulation that allows high-resolution phase retrieval without the need for lenses.
In this internship, you will develop and evaluate a coded lens-free ptychographic imaging system. The focus will be on investigating different coded surface concepts and exploring ptychographic reconstruction approaches to achieve improved resolution, stability, and imaging speed.
By the end of the internship, the student will gain experience in:
Computational imaging & lens-free microscopy
Optical system modelling and simulation
Ptychographic phase retrieval
Image reconstruction algorithms and optimization
Experimental optical coded surfaces and data acquisition
Working with imec hardware and Python-based reconstruction pipelines
Required Skills
Background in electrical engineering, optics/photonics, applied physics, or computer science.
Experience in Python .
(Optional but beneficial) Knowledge of Fourier optics, inverse problems, or machine learning.
Type of internship : Master internship
Required educational background : Electrotechnics/Electrical Engineering, Physics, Computer Science
The reference code for this position is 2026-INT-018. Mention this reference code in your application.
Applications should include the following information:
resume
motivation
current study
Description
In coded ptychography, a patterned layer positioned near the sensor introduces spatial modulation that allows high-resolution phase retrieval without the need for lenses.
Expected Learning Outcomes
By the end of the internship, the student will gain experience in:
Computational imaging & lens-free microscopy
Optical system modelling and simulation
Ptychographic phase retrieval
Image reconstruction algorithms and optimization
Experimental optical coded surfaces and data acquisition
Working with imec hardware and Python-based reconstruction pipelines
Required Skills
Background in electrical engineering, optics/photonics, applied physics, or computer science.
Experience in Python .
(Optional but beneficial) Knowledge of Fourier optics, inverse problems, or machine learning.
Supervising scientist(s) :
For further information or for application, please contact Zhenxiang Luo (Zhenxiang.Luo@imec.be) and Ziduo Lin (Ziduo.Lin@imec.be).
The reference code for this position is 2026-INT-018. Mention this reference code in your application.
Applications should include the following information:
resume
motivation
current study
Incomplete applications will not be considered.
#J-18808-Ljbffr