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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
engage with international and national partners across multiple institutions. Drive innovation in the design and development of miniaturized imaging technologies. Your profile Ph.D. in natural sciences
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offers the opportunity to collaborate with world-class researchers and contribute to international efforts in understanding the fundamental nature of the universe. Qualifications The Experimental Particle
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, Chalmers offers Swedish courses to help you settle in. Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note
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publications for peer-reviewed high level scientific journals Presenting research findings at international conferences and seminars Research visits with European partner universities and research facilities
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AI, Natural Language Processing, or clinical data analysis. Excellent analytical and problem-solving skills. Interest in collaborative research with both academia and industry. Good communication
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for colonisation, survival and transmission in the flea vector. This position is embedded within a collaborative project spanning the natural, medical and human sciences, with the broader aim of understanding
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publication thematically or methodologically related to the project; With active participation in international research conferences and professional fluency in English; Good French or Italian language skills
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research. We advance the understanding of dynamic processes to address global challenges, from mitigating the impacts of natural hazards and sustaining our habitat amid global change to responsibly managing
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collaborate with partners at ELLIS Institute Finland. Target publications at top-level AI, ML, and NLP venues. Who we are looking for Requirements Ph.D. in Machine Learning, Natural Language Processing
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XFEL, ESRF, APS, and LCLS, depending on awarded beamtime. The project is supported by the Independent Research Fund Denmark. More information about the research group is available here: https