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own surveys and secondary data collected by third parties. The ideal candidate for the position will be a recent PhD graduate with a deep interest in this domain who can provide research support in
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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are part of a sub-project on Algorithmic Sustainability in association with Professor Christina Lioma and her Machine Learning research team in the Department of Computer Science at the University
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globally recognised business school with deep roots in the Nordic socio-economic model. Our faculty has a broad focus on societal challenges, and we have earned a reputation for high-quality disciplinary and
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deep learning models, testing and optimizing the models documenting all performed tasks in detail, visualizing the model results, and writing technical reports investigating related software and
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chatbots and other virtual assistants that can help students learn more effectively or prepare for exams, or support teachers in repetitive tasks. We are looking for a highly motivated and experienced
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postdoctoral researchers. To collaborate with industry partners to apply research findings in practical settings. We are looking for candidates who: Possess deep knowledge of process engineering and wastewater
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deep roots in the Nordic socio-economic model. Our faculty has a broad focus on societal challenges, and we have earned a reputation for high-quality disciplinary and interdisciplinary research and
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quantitative and qualitative methods to generate systematic knowledge about business-government relations and international business relations. To learn more about the research and education of the department