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a step-change in our ability to observe, quantify and understand forest disturbances and recovery by using time series of the most detailed structural and radiometric 3D forest models ever built
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model of the ultrasound-sensitive hippocampal formation as environment. The candidate will develop surrogate models of the hippocampus to allow for more extensive optimization of the controller. Finally
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depth and EEG electrode measurements. Finally, the closed-loop ultrasound technology will be tested in the intrahippocampal kainic acid mouse model in this Ph.D. project. You hold a Master’s degree
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; You are interested in academic and/or project-based research and services; You have excellent laboratory skills in applied microbiology, and microbial and molecular techniques in general; You have
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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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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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: 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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nature and forests and a keen interest in forest ecology Keen to carry out fieldwork (Brazil, Belgium, UK and Australia) Previous experience with (terrestrial) laser scanning and 3D modelling is a plus
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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