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with no cure, and we urgently need new ways to understand and treat it. This exciting PhD project combines cutting-edge stem cell technology, 3D bioprinting, brain cell models, and advanced genomic
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Shape the future of cancer research with AI-Driven 3D spheroid model simulations! Join us! We are seeking a motivated PhD candidate to join our interdisciplinary team bridging experimental in vitro work
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preclinical evaluation in physiologically relevant 3D models. This PhD position sits at the interface of nanochemistry, and translational cancer research, and offers the opportunity to contribute to a next
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Empa within the framework of SURPASS are as follows: Volumetric prestressing of cast and 3D-printable SURPASS overlays using Fe-SMA fibres. Meso-scale finite element modelling of volumetric prestressing
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at the Department for Functional Materials in Medicine and Dentistry (FMZ) / Center of Polymers for Life (CPL), Julius-Maximilians-Universität Würzburg (JMU). The candidate will work on advanced 3D bioprinting and
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Can AI learn to reason like a human - and recognise when it isn’t sure? This PhD tackles that challenge in a high-impact setting: interpreting 3D digital models of rock formations built from drone
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with familiarity with foundation models (e.g. vision language models) and the ability to design and prototype innovative, reliable and reproducible solutions for complex 3D scene understanding tasks
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/or scNMT-seq workflow for multimodal profiling of melanoma models and tissue samples. The project will translate the protocol developed by DC3 into 3D melanoma organoid and immune cell co-cultures
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, 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
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are still present. This PhD research aims to develop new and efficient AI-based solutions for processing LiDAR data (2D/raster and 3D/point clouds) and improve the detection of sub-canopy archaeological