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information-seeking behaviour and to examine how these differences relate to learning in the classroom. A central aim is to translate insights from fundamental research on curiosity into educational practice
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datasets and an evaluation framework covering statistical fidelity, temporal and spatial structure, physical plausibility and downstream task performance (e.g. train-synthetic-test-real forecasting). You
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behaviour and to examine how these differences relate to learning in the classroom. A central aim is to translate insights from fundamental research on curiosity into educational practice. You will design and
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demonstrable experience with programming in Python and implementing statistical or machine learning algorithms. You have experience with software development practices such as testing and version control with
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evaluation framework covering statistical fidelity, temporal and spatial structure, physical plausibility and downstream task performance (e.g. train-synthetic-test-real forecasting). You will collaborate with
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better world (sustainable societies). We study and teach management at the level of public and private organisations. In this context, we examine how to balance economic, ecological, and social values in a
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datasets and an evaluation framework covering statistical fidelity, temporal and spatial structure, physical plausibility and downstream task performance (e.g. train-synthetic-test-real forecasting). You
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the scientific literature, recruit and test participants, analyse behavioural and neuroimaging data and write scientific articles that will form the basis of your dissertation. You will work closely with your