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of data-driven life science and includes access to a formidable package of resources. Project description: DDLS Fellows Program Data-driven life science (DDLS) uses data, computational methods and
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explores novel methodological approaches using survey and register data. Work tasks The work will focus on exploring and developing quantitative approaches grounded in intersectionality theory and with
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underlying physiological processes and pathological conditions. Meritorious Expertise in developing cutting-edge neurotechnologies, including advanced molecular methods, which not only improve data analysis
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their epigenetic repressors such as DNA methylation. Importantly, our preliminary data revealed significant alterations in this epigenetic repression as we age, posing one of the group’s main research questions: How
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advanced AI/LLM methods. The Staff Scientist will lead development of LLM-powered analysis and knowledge tools (e.g., retrieval-augmented generation over omics + literature, automated data-to-insight
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research experience in the field of informatics/information systems/HCI – human-computer interaction. Since employment as a postdoctoral fellow is a merit-based position for junior researchers, we primarily
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or English. The application must be made via our e-recruitment system Varbi and must be received latest 16 December, 2025. For additional information about the position, please contact Professor Lukas Kenner
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suitability for the project. A CV (Curriculum Vitae) including degrees, technical expertise, employment history, and names and contact information for two references. A list of publications. Contact Information
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questions about your motivation for applying and to describe your skills and experience relevant to the position. More information For more information, please contact Assistant professor Julio Diarte Almada
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the realization of practical devices in collaboration with industry. For information on relevant background research, please refer to our earlier publications: doi.org/10.1038/s41467-025-55954-3 and doi.org/10.1002