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set a course for the future – a future that you can help to shape. The EMAT research group at the Faculty of Science (University of Antwerp) is seeking to fill a PhD position on the development
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analysis, data modeling, and algorithm development. Experience with environmental analysis or microplastic research is a plus but not required. Strong analytical and problem-solving skills, ability
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
adaptation, speciation, and biological innovations. This project aims to redefine our understanding of gene loss alongside gene gain in plant evolution, focusing on developing novel genomic approaches
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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and grippers offer improved safety and adaptability but introduce new challenges in design and control. Their development is still largely bio-inspired and trial-and-error based. Integrating flight and
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and Delivery: Design and develop training programs on Data Science and AI topics, including machine learning algorithms, data visualization, and statistical analysis. Provide foundational sessions about
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for space logistics. With the development of mathematical models and optimisation algorithms, we aim to support strategical, tactical and operational decisions in the context of the deployment of in-orbit
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including other forms of 'smart' automation, such as algorithmic recommendation and chatbots. We are hiring a postdoctoral researcher to develop a project critically analyzing the role of AI in media and
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer