115 web-developer-"https:"-"https:"-"Institut-Agro-Rennes-Angers" PhD positions in Denmark
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(LLMs) to explore historical text data and cultural heritage collections. Collections of historical texts are increasingly used to train AI, but, consisting of highly heterogeneous text data
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to the development of background-suppression techniques for single-photon detectors used in axion experiments, operating at optical and infrared wavelengths. The research project includes the installation and
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Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship – to develop and support implementation strategies that address
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power electronics to enhance the reuse and recycling of components, enabling a more circular life cycle. The work will contribute to a new paradigm in the development of power electronics that incorporate
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nanosatellite/CubeSat constellations and to develop innovative GNSS-based sensing methods and AI models to detect a variety of Earth surface processes. This PhD position focuses on developing analytical models
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research activities. In close collaboration with colleagues across the department, the position holder will contribute to maintaining and further developing an infrastructure that delivers state of the art
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focused? Then this PhD position may be just right for you. We will support you in developing the right research competencies for a career in industry or academia. We offer a PhD journey for three years
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Communication, the Faculty of Social Sciences and Humanities and the Center for Clinical Data Science (CLINDA), Department of Clinical Medicine, the Faculty of Medicine. AI:GENE-XPLAIN develops AI tools
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, industrial, or translational careers while contributing to personalized and clinically relevant therapeutic solutions. Responsibilities and qualifications The main purpose of this PhD position is to develop a
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, the projects combine classical microbiology, microbial physiology, experimental evolution, and omics-based approaches to link microbial interactions and system performance across spatial and functional scales