Sort by
Refine Your Search
-
Employer
-
Field
-
neuroscience. We are part of the Division of Cell Biology, Neurobiology and Biophysics within the Department of Biology . Our division hosts the state-of-the-art Biology Imaging Center , which offers technical
-
for automatic segmentation and morphometry of histological images; - Compare the predictive value of AI-driven image analysis with clinical and biomarker data; - Collaborate with international experts in medical
-
learning has strong potential for computer vision, from hyperbolic image segmentation [2] to hyperbolic tree embeddings [3] and hyperbolic vision-language models [4,5]. [1] Nickel, Maximillian, and Douwe
-
using deep learning and AI-driven image analysis. You will: - Analyse pre-implantation kidney biopsies according to the Banff criteria; - Apply AI methods for automatic segmentation and morphometry
-
geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
-
for controlling protein levels and guiding development. In the Ruijtenberg lab, we study these mechanisms using a combination of genome-wide sequencing and single-molecule imaging approaches, aiming to understand
-
readiness of these smart materials is still low, which makes their integration in a smart material system with various segments a challenging design assignment. Therefore, it needs elaborative testing and
-
other viruses, including the coronaviruses, using the latest imaging techniques to track how they replicate. He is also investigating the ‘arms race’ between the virus and the host’s immune system, how