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ESR 1 : Teun Huijben

I started my studies with the bachelor program Nanobiology at the Delft University of Technology and Erasmus MC Rotterdam. After my bachelor’s degree, I continued in Delft with a double master’s degree in the programs Nanobiology and Biomedical Engineering.

During my studies, I got fascinated by microscopy. Next to the practical aspects, I am especially interested in improving microscopy by using computational algorithms, that involve image/data analysis, computer vision, machine learning, and pattern recognition. I did an internship in the experimental group of Daan Brinks at the TU Delft where I designed and constructed a two-photon microscope. As a second internship, I went to UC Berkeley for a few months to work in the group of Ahmet Yildiz. And to conclude my Master’s, I conducted my thesis research in the computational group of Bernd Rieger and Sjoerd Stallinga at the TU Delft where I developed and implemented classification algorithms for single-particle averaging of single-molecule localization microscopy data.

Within SuperCol I hope to build on these interests and bring localization microscopy on colloidal nanoparticles to the next level.

Project topic: Improving localization microscopy on colloidal particles using deep learning

In my project I will extend localization microscopy to colloidal particles by developing data-driven models, using deep learning, to retrieve the accurate position of a fluorescent label on colloidal particles. The models, that are trained on experimental data obtained by other researchers within the network, will subsequently help other researchers to predict accurately the position of functional groups on nanoparticles.

 

Home country:

The Netherlands

SuperCol partner:

Technical University of Denmark (DTU)

Supervisor:

Dr. Kim Mortensen

Starting date:

September 15th, 2020

Publications: 

Meetings:

  • SuperCol kick-off meeting, November 2020 (online)

Secondments:

  • Max Planck Institute for Polymer Research, Germany [2021]
  • Nanoseedz, Hong Kong [2022]
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