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Field
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). The doctoral fellow will be employed at Hannover Medical School (MHH) and benefit from international mobility opportunities, collaborative research across the RAMP-UP network, secondments, and a structured
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
hydroacoustics, bioinformatics and/or image analysis (ZooScan, UVP) Excellent analytical skills, including statistical modelling, mathematical modelling and network analysis Proficiency in coding (R, Python
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Arts, e.g., maintaining the alumni network and the cooperation network, and managing the future Art Education website Participation in academic self-governance Further development and promotion
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bioinformatics, and a strong willingness to collaborate are also expected. Close cooperation with the Transdisciplinary Research Area “Life and Health” and other research networks, and a thematic alignment with
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interactions. • Integration into established national and international research networks and opportunities to present your work at leading scientific conferences. • The opportunity to publish your research in
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position is limited to 3 years and is starting no later than February 1, 2027. The position is part of the Max Planck Artificial Intelligence Network . Under the supervision of Prof. Iyad Rahwan, your
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priorities of the Department of Mathematics and Computer Science by establishing a dedicated research group on optimization and will actively participate in research networks and initiatives within
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to excellent scientific and technical facilities for your work Networking & Exchange: You will participate in (international) conferences and project meetings and actively build your scientific network
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application of advanced Large Language Models (LLMs) to systematically code rich qualitative case narratives. This AI-assisted case-survey method enables rigorous large-N cross-case comparison, preserving
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of advanced Large Language Models (LLMs) to systematically code rich qualitative case narratives. This AI-assisted case-survey method enables rigorous large-N cross-case comparison, preserving contextual depth