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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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challenges and opportunities (or willingness to learn) has understanding of benefit sharing in payment for ecosystem services (or willingness to learn) preferably has fieldwork experience (in the Global South
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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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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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., 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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motivation to learn, cryo-EM data collection, image processing, and 3D structural analysis. Prior experience with cryo-EM single-particle analysis (SPA) and/or cryo-electron tomography (cryo-ET) is a strong
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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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consortium; form interdisciplinary collaborations across fields and geographical locations within the Netherlands; acquire skills by active participation in science communication activities, interacting with