120 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD scholarships in Belgium
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approach, combining machine-learning–enhanced text-as-data analysis with qualitative discourse analysis. The project aims to produce a set of high-quality scholarly outputs, including peer-reviewed journal
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fully funded PhD position in machine learning, AI, and data science for public health within the Electronics & Informatics Department (ETRO) of Vrije Universiteit Brussel (VUB). The PhD is embedded in
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machine learning processing of the spectroscopic data • The optical design and development of novel custom spectroscopic sensors benefitting from freeform optics. • Integration of the in-situ
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-spectral microscopy framework that extracts meaningful spectral information from a single image, by combining innovative optical system design with learning-based data processing. The research aims
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fairness and inclusion, racialized students often face barriers that harm their learning and well-being. Research has revealed many causes of these inequalities, such as socio-economic disadvantages
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or are willing to learn Dutch quickly. In your application, you demonstrate that you are capable of doing so. You are strong in planning and organizing and can work independently. Your teaching competences are in
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attention to quality, integrity, creativity and cooperation. You have a strong background in signal processing, with emphasis on acoustics, array processing, or time–frequency analysis. You are eager to learn
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immunology (e.g. in vivo models, flow cytometry, imaging) Motivation to learn and apply computational biology/bioinformatics approaches (training will be provided). Some background in programming is therefore
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. You are a practical problem solver, are hands-on and eager to learn. You have strong oral and written English proficiency. You have excellent interpersonal skills to collaborate constructively and
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, molecular biology, or related disciplines FELASA certification Experience with or highly interested in experimental immunology (e.g. in vivo models, flow cytometry, imaging) Motivation to learn and apply