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a PhD in biology, earth system or data science, or a similar field, and have several years of experience with interdisciplinary collaborations focused on understanding biodiversity dynamics by
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recognition events to colonization strategies. Within this framework, the advertised postdoctoral project is specifically focused on complex data analyses of plants for improved symbiotic associations with soil
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on the successful award of the PhD degree. Who we are CLINDA is a multidisciplinary center dedicated to bridging clinical practice and data science. It comprises three research groups: (1) Clinical AI, (2
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local and regional trends. The necessary samples and data have been collected in recent years during expeditions to the area, and include numerous sediment cores, acoustic surveys of the seafloor and sub
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
The Department of Digital Design and Information Studies within the School of Communication and Culture at Aarhus University invites applications for a postdoctoral position “Human AI Collaboration
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as part of a running team including two PhD students. Your profile Applicants should hold a PhD in molecular biology, genetics, epigenetics, developmental biology, or a closely related field
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strategies and market positioning. Job description The successful candidate is expected to contribute to the overall objectives of the project by being involved in design, implementation, data collection, and
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to think independently, in human-AI interaction. You will connect the project's technical work with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction
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. Your competencies You hold a PhD degree in mechanical engineering or a closely related field, and you have a strong background in solid and computational mechanics. You have solid experience with finite
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diffraction experiments on a wide range of materials Program and establish analytic tools to assess data quality Support users in experiment planning, sample preparation, data analysis, and structure