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and automata, and the interaction between formal methods and artificial intelligence. We welcome candidates interested in topics ranging from foundational theory to the development and evaluation
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these methods across different crops to identify conserved patterns of stress resilience 4. Identify candidate genes associated with key agronomic traits related to resilience 5. Contribute to software and web
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environments, design-based research methods, digitalization and AI preferable in higher education, but background in K-12 studies might also be of relevance. Applicants with PhD thesis that involves studies
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disse informasjonskapslene. Databehandlingsansvarlig: HAProxy software Formål: Kreves for at nettsiden skal fungere riktig. Personvernregler for databehandling: HAProxy software - Personvernregler
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bicc - Bonn International Centre for Conflict Studies gGmbH | Bonn, Nordrhein Westfalen | Germany | 7 days ago
requirements: A completed PhD in Political Science, Peace and Conflict Studies, Migration Studies, Refugee Studies, Development Studies, International Relations, Social Anthropology, Area or Cultural Studies
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proximity to Dr. Rodrigues’s office will facilitate frequent informal interactions, supplemented by at least one formal meeting each week and regular multidisciplinary project meetings. The fellow will
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, Trustworthy AI, Software Engineering, and Cybersecurity. The group is developing novel methods, tools, and platforms to support the safe deployment of AI systems in real-world environments. Current research
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EXPERIENCE in: Scientific/Academic writing Research methodology (Quant or Mixed Methods) Experience with statistical software (e.g., R, Mplus, SPSS, etc.) Credentials must be obtained prior to the start date
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. The role You will contribute to the design and implementation of the ABLE platform, including software development, possibly some hardware prototyping, and evaluation with users. A key focus will be
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. The postdoctoral associate will be expected to work both collaboratively and independently on research projects, advancing computational methods using machine learning, developing automated pipelines for data