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a strong interest in and/or experience with quantitative research methods, including psycho-physiological and behavioral measures and advanced statistical (and/or machine learning) methods. You have a
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complex omics data. Therefore, knowledge of programming languages such as Python or R is necessary and prior experience with data science, high-throughput omics, Linux command line, machine learning and
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that combines machine learning and knowledge-based inference. In real-world applications, it is often paramount to exploit expert knowledge for the task at hand. However, this poses significant challenges with
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), user interface design, or data visualization techniques. Familiarity with frameworks for explainable machine learning (e.g., SHAP, LIME, Captum, Alibi). Experience in designing context-aware, adaptive
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representations in non-associative and associative learning and delineate the pathways and neuromodulatory systems underlying novelty-evoked exploratory behaviors. The research should integrate cutting-edge
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interdisciplinary research project at IDLab-MEDIA (https://media.idlab.ugent.be/ ), UGent – imec, aimed at advancing the state of the art in motion capture, sensor fusion, immersive media, and 3D computer vision
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, trustworthy, and fully explainable. The project introduces Generative Learning Cognitive Services (GLCS), intelligent, modular CPS components combining generative eco-cognition, cognition-oriented proactivity
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in an academic environment for a 4 years period in view of a PhD degree. • You have a strong background in wireless and mobile networks and machine learning • You have excellent coding skills; hands
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physical principles into the learning process to maintain physical consistency outside the training domain. This PhD research is envisioned to result in a breakthrough in the application of machine learning
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(4 years), likely in cooperation with external partners (academic and/or industrial). You work on AI (i.e., analytics, modeling, machine learning) for energy applications, mostly focusing on