Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Maastricht University (UM)
- Leiden University
- Radboud University Medical Center (Radboudumc)
- Wageningen University & Research
- ARCNL
- University of Amsterdam (UvA)
- University of Groningen
- Utrecht University
- Amsterdam UMC
- Centrum Wiskunde en Informatica (CWI)
- HFML-FELIX
- Naturalis
- Radboud University
- Royal Netherlands Academy of Arts and Sciences (KNAW)
- Sanquin Blood Supply Foundation (Sanquin)
- Tilburg University
- University Medical Centre Groningen (UMCG)
- University of Twente (UT)
- 10 more »
- « less
-
Field
-
-inspired computing paradigm with the potential to drastically reduce energy consumption while enabling faster inference than conventional digital architectures. A major challenge, however, is the development
-
households or companies. But energy data is not like images or text: it consists of time series living on a physical network, governed by power-flow equations. Off-the-shelf generative models produce data
-
accurate despite the large temperature gradients present in cryogenic experiments. You will explore full-field techniques such as digital image correlation, speckle and grid methods, interferometry, digital
-
machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these
-
-agent" that integrates multimodal health data, including MRI examinations, PSMA PET/CT imaging, histopathology results, and longitudinal electronic health records, to support clinical decision-making in
-
fundamental learning procedures to tackle distressing images related to aversive memories. The aim is to generate insights with direct impact on clinical practice and patient wellbeing. PhD Candidate Reducing
-
Description Do you wish to join the new Marie Sklodowska-Curie Action Doctoral Network PREFERENCE and help us make a transformative difference in the field of molecular imaging? Then, apply to join the
-
PhD candidate, you are expected to bring your own creativity to the challenge: How can image-based AI analysis reveal drug effects? How can mechanistic computational models develo on spheroid morphology
-
mitotic errors in human IVF embryos from live cell imaging data. In addition, you will contribute to teaching activities (maximum 0.1 FTE) and supervise Bachelor and Master students. This project is
-
PhD in Optical Characterization and Photonic Performance Analysis of Liquid Crystal Polymer Coatings
between material development, optical modelling, and prototype integration. Information You will: characterize one-way transparent cholesteric liquid crystal polymer films and switchable photonic coatings