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experiments using cancer and stromal cell models, including CRISPR/Cas9-based genetic approaches to investigate Cx43-dependent mechanisms. Establish and characterise tumour–stromal co-culture and 3D models
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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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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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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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safety, combining simulation, laboratory testing, and in-orbit validation. The candidate will create dynamical and photorealistic 3D models of the tether and spacecraft to support both engineering analysis
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therapeutic targets and strategies to improve clinical outcomes. The successful candidate will develop skills in 3D cell culture models, multi-omics and more. We are seeking a highly motivated candidate with a
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objective of developing 3D laser processing strategies for aerodynamic bearings with enhanced tribological performance. The doctoral candidate will: Leverage and extend KU Leuven’s state-of-the-art ultrashort
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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
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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and synthesize via light-based 3D-printing architecture (meta)materials for medical soft robotics applications. Furthermore, the morphology, microstructure, and mechanical behaviour of the metamaterials