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into account typological and technological variability, changes in raw material preferences, as well as the spatial distribution of the finds within their respective find contexts). In addition, you will assist
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involve designing advanced algorithms that efficiently utilize UWB signal features (RSSI, channel impulse response, phase and amplitude data, Doppler maps,..) to support both high-precision localization and
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learning algorithms. The two PhD students hired through this vacancy will primarily contribute to the development of debiased learning methods and assumption-lean modeling tools, and their application
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. Construct a model-based collision detection algorithm that exploits this mechanical compliance. Evaluate vibration dampening techniques in collaboration with the researchers from VUB. Design a hybrid robot
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. Digital Extraction from Historical Taxonomic Literature Application of OCR and machine learning algorithms to digitize printed and handwritten documents; Linking specimen mentions in literature to digital
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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
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to study effects of (TI)-DBS on ex vivo brain slices and in vivo rodent models. Develop advanced closed-loop neurostimulation algorithms. Engage in a cross-disciplinary team, collaborating with experts
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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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omnipresent in many application domains: from listening podcasts on headphones and providing an assistive listening experience via hearing aids, to achieving audio distribution in venues. You will be performing