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wireless components as intentional parts of the built environment; using making-based and cross-disciplinary design methodologies (inspired by CM³) to prototype lightweight "contact service points
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neurodevelopmental conditions, by bridging disciplines, from artificial intelligence, microelectronics, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell
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immunology (e.g. in vivo models, flow cytometry, imaging) Motivation to learn and apply computational biology/bioinformatics approaches (training will be provided). Some background in programming is therefore
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. This is still a very new research topic and many scientific questions remain unanswered. Alongside the modelling research, there will also be a measurement campaign using high-speed imaging and in-line
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advanced optical imaging, to characterize materials and measure cellular mechanics. Collaboration and Expertise You will work closely with our expert collaborators: Prof. Rob Jelier (Computational Biology
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, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell biology in human and animal models. Doing a PhD at our Center Embedded within both VIB and KU Leuven, we
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, molecular biology, or related disciplines FELASA certification Experience with or highly interested in experimental immunology (e.g. in vivo models, flow cytometry, imaging) Motivation to learn and apply
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voiding behavior in mice and developed live imaging techniques to visualize sensory signaling in the bladder wall and dorsal root ganglion (DRG) neurons. In addition, we explore these pathways in human
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adults, significantly impacting quality of life, and remain challenging to treat. Our research group has pioneered innovative methods to study voiding behavior in mice and developed live imaging techniques
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Bonus but not required Experience in imaging or spatial omics data