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microfluidic chip to simulate inter-organ crosstalk and dynamic hormone regulation. A panel of environmentally relevant chemicals and mixtures will be applied to evaluate dose–response effects and mechanisms
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quantitative image analysis, numerical modeling, and explainable AI (XAI) with state-of-the-art biophysical methods. Using techniques such as traction force microscopy, microfluidics, 3D bioprinting, and
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning
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milli-/microfluidic reactive experiments relevant to the DLRI process. • Implement and optimize ZnO nanoparticle synthesis under controlled conditions. • Perform optical measurements (UV-Vis, PL) and
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also be subjected to droplet microfluidics, one of the most promising high-throughput methods for effectively processing the MIP-probe-positive individual cells for RNAseq analysis by using our standard
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; wearable physiological sensors; point-of-care diagnostic devices; biosensors for disease detection; portable and miniaturized diagnostic platforms; microfluidic-based biosensing systems; image-guided
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effectiveness and safety. This PhD project aims to address this challenge through biomimetic engineering design, combining predictive in silico modelling with machine-learning techniques and microfluidic
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response especially with applications in microfluidics, organ-chip, and microphysiological systems. Hands-on experience with research protocols relating to human endothelial cells and neutrophils is required
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. Requirements: PhD in Vascular Biology, Cell Biology, Mechanobiology, or a related field Solid expertise in vascular biology, ideally complemented by knowledge of mechanobiology and microfluidic engineering
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perform functional readouts such as calcium imaging and electrophysiology. Where to apply Website https://www.academictransfer.com/en/jobs/356705/phd-researcher-development-of-h… Requirements Specific