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that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
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consortium; form interdisciplinary collaborations across fields and geographical locations within the Netherlands; acquire skills by active participation in science communication activities, interacting with
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weather prediction using Machine Learning approach (hybrid forecast). The app is also expected to be equipped with seasonal forecast for agricultural planning. You will co-design the short-, medium-, and
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Fundamental Techniques in Table Representation Learning in collaboration with the University
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, quantitative or mixed-methods); Independent thinking and critical analytical skills; Good collaboration skills and an ability to join interdisciplinary and intercultural academic communities; Excellent oral and
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PhD position within the project "What's wrong? Ancient corrections in Greek papyri from Egypt" (AnCo
an excellent opportunity to study the Greek language as written by non-scholarly writers in antiquity. This project will collect, annotate and study the ancient corrections in this corpus to learn more about the
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data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain
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scientific conferences. • Actively participate in and contribute to the Fertile Soils project. • Build and maintain contacts with internal and external partners. • Teach courses in the Faculty of Spatial
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internally, so while you learn the intricacies of our industry, you’ll have plenty of opportunities to contribute and directly affect our bottom line within your first few weeks on the team. While interest in
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University. Requirements A master’s degree in (applied) mathematics (or related), with a strong background in computational methods, preferably also using computational frameworks for machine learning in