Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
of human cohorts” (65%, Proteomics Group) Ref. Number: 396_2026 PhD Position 3 “Image-based analysis of human cohorts” (65%, Lipidomics Group) Ref. Number: 397_2026 PhD Position 4 “Data Science” (100
-
, by integrating image analysis and docking across multiple structural states. The new tools will be validated through their application to VCP/p97 data, a key protein that plays a central role in
-
for cryo-electron microscopy (cryo-EM) data analysis, modeling conformational heterogeneity, and identifying optimal binding candidates, by integrating image analysis and docking across multiple structural
-
to develop a hyperspectral DUV imaging system for applications in microscopy in the context of chiral light-matter interactions at the nanoscale as part of our team at the VU Amsterdam (matzlab.com
-
The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
-
computational enhancement. Once operational, you will focus on high-resolution imaging and nanoscopy. Your duties doing research towards writing a PhD thesis develop and optimise DUV microscope at the absolute
-
at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 18 days ago
Engineering, Computer Science, Applied Mathematics or a related field. - A strong background in image processing or/and in computer vision is required. - Strong programming skills in Python. - Strong
-
target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing on the glioblastoma infiltrative
-
Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes