Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
-
Field
-
tissue reconstruction. The PhD candidate will work with multimodal datasets from biological tissues and engineered biomaterials and contribute to research on: quantitative 2D and 3D analysis of biological
-
Job related to staff position within a Research Infrastructure? No Offer Description Neural reconstruction pipelines (e.g. Gaussian Splatting) and 3D sensing technologies such as LiDAR and
-
, and regenerative constructs. The project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine
-
, generative AI, and blood flow modeling. You will: develop deep generative models (such as latent diffusion models, implicit neural representations, and flow matching) for uncertainty-aware 3D reconstruction
-
interpreted using deep learning to estimate tool-to-retina distance and generate accurate three-dimensional navigation commands without relying on conventional 3D reconstruction. Research Objectives
-
, advanced acquisition strategies, multi-static beamforming methods, and semi-tomographic reconstruction algorithms that enable high-quality 3D visualization of the abdominal aorta. In addition, you will
-
representations, and flow matching) for uncertainty-aware 3D reconstruction of coronary anatomy from 2D X-ray angiography; develop physics-informed neural networks and graph-based neural operators for fast
-
-static beamforming methods, and semi-tomographic reconstruction algorithms that enable high-quality 3D visualization of the abdominal aorta. In addition, you will develop algorithms for segmentation
-
specially developed, AI-based software that enables 3D reconstructions of element distribution Complementary analysis using other advanced techniques such as SIMS, Raman, FIB-SEM, µ-CT, etc. Compilation
-
AI systems for real-time 3D mapping on compact, low-power devices. The project will combine optical sensing, event-based vision, and radio-frequency (RF) data with advanced AI to build robust mapping