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spatial structures, physical laws, high-dimensional imaging, and clinical covariates. Apply these methods to spatial transcriptomics and fluorescence imaging data to gain a more precise understanding of
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at the cellular level, and (iii) applying quantitative image analysis to compare structural organization across fertile and infertile donors. The project is embedded in an active collaboration with a local
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. They have led to a plethora of important downstream applications, such as image and material generation, scientific computing, and Bayesian inverse problems. At the core of these models are differential
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: Łukasiewicz Research Network – PORT; project leader: Marcin Poręba, PhD, DSc, Prof. of WUST. The PACMAN project aims to develop a new class of antibody–drug conjugates (ADCs) that do not require internalization
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-based imaging technique Dark-Field X-ray Microscopy. Installed at the European Synchrotron Radiation Facility in France we utilize it to visualize the evolution of internal structures in metals during
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relate to processing-relevant traits such as fry quality, yield, and waste? The project will take an integrated approach combining advanced imaging, quantitative phenotyping, and genetics. A high
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• Integration of physiological and biochemical data with advanced phenotyping approaches (e.g. ther-mal imaging) • Statistical analysis and interpretation of multi-factorial datasets • Active collaboration with
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will validate. You will derive model parameters from experimental imaging and use inverse modeling techniques to measure microthrombi deformation under flow. Hybrid Research: You will study wall
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, actuation, and control. The research includes the design, fabrication, and experimental validation of micro-scale robotic platforms, integration of optical and imaging-based feedback, and development
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multidisciplinary environment at the interface between academia, clinic, pharma industry, where resources and expertise in human biobanking, omics data, imaging, animal surgery and molecular biology methods will be