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to developing methods for iPSC culture, 3D cell models, and stem cell differentiation within the field of complex tissue regeneration. In this PhD project, you will work at the interface of stem cell biology
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imaging (crucial) Experience with image segmentation, deep learning, or computer vision. Experience with 3D image processing or inverse problems. Experience with experimental research and data acquisition
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to developing methods for iPSC culture, 3D cell models, and stem cell differentiation within the field of complex tissue regeneration. In this PhD project, you will work at the interface of stem cell biology
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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3D X-ray inspection techniques for industrial quality control. The project is foundational in nature, while at the same time exploring applications in collaboration with industry partners. The main
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
for the AMBIOM (Analysis of Microscopic BIOMedical images) Research Group: PhD Candidate (m/f/d) You will be responsible for Developing large-scale microscopy image analysis pipeline for 3D microscopy images
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differentiating these stem cells into organ specific cell types and 3D organoids together with CRISPR technology, you will study how genetic variants shape cellular responses to chemical exposure. Combined with
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characterization of materials’ magnetic, electronic and structural properties. Experience in spectroscopy and microscopy is valuable Knowledge in programming (Python) and 3D modelling will be valuable Availability
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methods and GIS tools to create 3D environments that integrate high-resolution 3D urban models with climate-resilience objectives. This should help policymakers and citizens optimize energy-efficiency
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the OPUS-LAP grant: "3D Genome Reorganization During Induced Cellular Senescence in Pancreatic Cancer: Insights from Single-Chromatin Fiber Analysis" Grant No. 2024/55/I/NZ5/03165. Where to apply E-mail