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position as a hub for innovation and learning. Located in the vibrant city of Groningen in the northern Netherlands, it attracts talent from across the globe. Located within the University of Groningen
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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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renovation construction work · evaluate (numerical or data driven) solutions for automated coordinated planning · develop and evaluate self-learning interactive visualisation technologies
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the same time, you will teach (20%) academically. Your teaching activities will take place within the programmes and courses of the Law & Markets Department. The particular teaching tasks will be decided
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scientific programming and numerical / statistical analysis of simulated and observed data. Candidates should be able to demonstrate motivation and a strong eagerness to learn, and have the ability to both
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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referring to the collective and organised pursuit (responsible governance) of a better world (sustainable societies). We study and teach management at the level of public and private organisations. In
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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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., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students
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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