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research project; ”Exploiting the genomic architecture of ectopic calcification: from variants to genome-guided therapy, using pseudoxanthoma elasticum as a model." Mineralization of soft tissues such as
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nematode community to N mineralization and N2O emissions in realistic soil conditions. In this project, we will set up unique multitrophic experiments controlling for the presence of specific trophic groups
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officially registered/enrolled at Ghent University as a student, you are automatically insured, within the policy conditions, • for personal physical accidents during university activities, • for personal
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-spotted spider mite, is among the most harmful pest insects worldwide. Due to its exceptional ability to adapt to various crops and pesticides, this mite serves as an excellent model system for studying
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: the aluminum oxide layer is fully recyclable. As a PhD student, you will contribute to the development of multiphysics (electromagnetic & thermal) models for windings of electric motors. Also, you will study how
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preclinical experiments on ex vivo brain slices and in vivo rodent models to investigate and optimize the effects of TIS Analyze ex vivo and in vivo electrophysiological and fMRI imaging datasets Collaborate
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, storage and demand. YOUR TASKS You will develop mathematical models and metaheuristic algorithms for complex optimization problems in the context described above, see e.g., https://arxiv.org/abs/2503.01325
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combined with an interdisciplinary toolbox drawing from ecology, forestry, and climatology. These data will then feed into cutting-edge joint species distribution models to project European forest plant
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wireless technologies. You implement the designed solutions on embedded hardware platforms and experimentally validate their performance. Experimental validation can be backed by modelling or theoretical
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. Defining predictive tasks based on clinical goals. Selecting and setting up appropriate data preprocessing pipelines. Training and evaluation of computer vision models. Internal and external algorithmic