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conducted through an open competition in accordance with the FIRST TEAM FENG Scholarship Regulations. Principal Investigator: Dr Barbara Pucelik Project description The project aims to develop an innovative
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PhD Scholarship Develop AI and machine learning models to guide real-time, personalised treatment of paediatric brain cancer using multiomics and clinical data, within the internationally
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research interests; the candidate's previous education and research experience; the alignment of the proposed research with the objectives and tasks of WP5; the available supervisory capacity within
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the Danish Cancer Institute in Copenhagen, and you will have the opportunity to undertake a research stay in Copenhagen. You will be part of a cross-disciplinary team of cell biologists and bioinformaticians
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statistics, engineering physics, physics, machine learning, or in a similar subject, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network
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research will focus on what happens when generative AI becomes part of everyday organisational life. You will study how early-career employees learn their jobs, seek help, develop expertise and deal with
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commensurate with experience but competitive. Type of Position Student Position Time Status Full-Time Required Education Ph.D. in Immunology, Cell Biology, Molecular Biology, Biomedical Sciences, Microbiology
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sustain learning as technologies develop. Through case studies of AI policy, the project identifies capacity constraints and develops affordable feedback processes, open tools and exchanges between agencies
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with experience but competitive. Type of Position Student Position Time Status Full-Time Required Education Ph.D. in Immunology, Cell Biology, Molecular Biology, Biomedical Sciences, Microbiology, Stem