Coded Ptychography for Lens Free High Resolution ImagingMaster internship - LeuvenExplore 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 microscopyOptical system modelling and simulationPtychographic phase retrievalImage reconstruction algorithms and optimizationExperimental optical coded surfaces and data acquisitionWorking with imec hardware and Python-based reconstruction pipelinesRequired SkillsBackground 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 internshipRequired educational background: Electrotechnics/Electrical Engineering, Physics, Computer ScienceThe reference code for this position is 2026-INT-018. Mention this reference code in your application.Applications should include the following information:resumemotivationcurrent studyDescriptionIn 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 OutcomesBy the end of the internship, the student will gain experience in:Computational imaging & lens-free microscopyOptical system modelling and simulationPtychographic phase retrievalImage reconstruction algorithms and optimizationExperimental optical coded surfaces and data acquisitionWorking with imec hardware and Python-based reconstruction pipelinesRequired SkillsBackground 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:resumemotivationcurrent studyIncomplete applications will not be considered.
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