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area of finance including scholarships within special focus areas. These special focus areas include big data in finance, pension finance, and household finance. The application process is a joint
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to the development and validation of novel blood-based biomarker assay. Mechanistic studies will be conducted in a neonatal large-animal model of cholestatic liver injury, where the student will participate in in vivo
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equipment in large structure environment, it is necessary to have access to a map of its topology, which may be based on BIM data (if existent) and floor plans or must be generated from collecting and
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laboratory, saving time and money. To this end, novel equipment allows testing and the collection of experimental data. To support this goal, we are looking for a colleague who is independent, who thrives
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scale in the laboratory, saving time and money. To this end, novel equipment allows testing and the collection of experimental data. To support this goal, we are looking for a colleague who is independent
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for working within an interdisciplinary research team Strong analytical skills and ability to work independently Ability to convert experimental data into useful functioning models Preferred qualifications but
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have an interest in quality news and AI-based chatbots. We expect: A Master’s degree in either computer engineering or computer science/data science. Experience with AI, Large Language Models, RAG, data
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communication and social skills for working within an interdisciplinary research team Strong analytical skills and ability to work independently Ability to convert experimental data into useful functioning models
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analysis, so computer vision experience is a requirement. Experience with large language models is a plus. Furthermore, as AI:Epertise is about deploying AI in the real world, we are looking for people with
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Cooling systems are essential for modern society - from server rooms and data centers to food storage and thermal comfort - yet they are also large energy consumers. This PhD project aims to make