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investigation. Being part of a larger collaborative project, the postdoctoral researcher will be involved into discussions within a broad range of fields including computational, medicinal and organic chemistry
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data-driven infection research, such as the development or innovative application of computational tools to analyze and integrate data or mathematical models to understand complex systems. Experience
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, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modeling of pathogen biology or host
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(connected to e.g. geolocation, wood quality, BIM models, EPDs, moisture and weather exposure), identify needs and collect complementary data and investigate techniques for connecting and transferring data
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, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modeling of pathogen biology or host
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our
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research, addressing the big data and artificial intelligence challenges of our industry partners. Field of subject for the position: Computer Science Placement: Department of Computer Science and Media
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The position's field of research focuses on developing and implementing safe, transparent, and explainable AI systems using multimodal deep learning and Large Language Models (LLMs) for healthcare
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postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological capabilities, with a profound potential impact for Europe’s next generation of research and
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large