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Field
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engagement, and ethical, regulatory and health-economic aspects of therapy development. The network will train a cohort of doctoral candidates in an international and interdisciplinary environment, combining
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learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and tissue reconstruction. The PhD candidate will work with
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. Ability to develop, understand, and critically evaluate machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal
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. The post would particularly suit a researcher with practical experience in cancer cell culture or proteomics but is open to anyone with a strong drive to develop methodological expertise in
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Development Plan (PCDP) outlining research objectives, timelines, skill development goals, and career aspirations. Organize, prepare and follow up biannual meetings of the supervisory teams. Design and conduct
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about being a Lund University employee: Work at Lund University Work description As a doctoral student, your primary responsibility will be to pursue third-cycle education through research projects aimed
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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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how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across
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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