
Teun Huijben
@teunhuijben
Scientist/PostDoc at Chan Zuckerberg Biohub (@czbiohub), San Francisco 🔬 image analysis | localization microscopy | machine learning, 🇳🇱 by bike 🚲
ID: 1276434335122546688
26-06-2020 08:37:27
118 Tweet
334 Followers
413 Following


Check out the preprint, videos (😍!) and amazing Github repo of #Ultrack: robust cell tracking under segmentation uncertainty! Wonderful work by Jordão Bragantini, I am glad to have been able to help on (and learn from) this in my first months at Chan Zuckerberg Biohub Network🚀


Unlocking the potential of nanoparticles in biosensing and drug delivery! This method enables super-resolution microscopy of nanoparticles revealing their detailed surface functionalization. #Nanotech DTU Health Tech TU Eindhoven Read it here 🔗 go.acs.org/bkt


📣Excited to share inTRACKtive📣: a web-based tool to visualize, analyze, and share cell-tracking datasets - in real-time, in your browser, without downloading a single file Check Loïc A. Royer 💻🔬⚗️'s thread below and explore our embryozoo.org or your data!🐭🪱🐠 #I2K2024


Do you want to use super-resolution microscopy to understand how biomaterials instruct cellular behavior? We have an exciting #PhDposition in the Biomaterials and Tissue Biomechanics Section TU Delft. Together with Amir A Zadpoor. For more information see👇careers.tudelft.nl/job/Delft-PhD-…



Join us next Friday at UC San Diego for a day full of microscopy🔬 , mass spec, and AI! Shout out to Uri Manor 💔 for putting this together! I will present our recent work on cell tracking algorithms and visualization with #Ultrack and #inTRACKtive #CellBio2024

Happy to be in sunny☀️San Diego for ASCB Cell Bio! Tomorrow I will present #Ultrack and #inTRACKtive (poster B513) at 11:15 am. Swing by the Chan Zuckerberg Initiative booth (#119) for live demos of these tools + #napari & #zebrahub 🐠 Looking forward to connect!🤩 #CellBio2024 #ASCB24 #celltracking



🚫 No dyes. No bleaching. 🔬 Just AI + label-free microscopy = vivid virtually stained images New in Nature Machine Intelligence: A deep learning model that enables robust virtual staining across microscopes, cell types & conditions. #CZBiohubSF Shalin Mehta explains:
