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within the area of visual and performing arts in Music and Modern Languages and Cultures. The Department of Engineering could host a fellow in environmental engineering within the Smart Soils Team and who
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. These are Classics and Ancient History; English and Comparative Literary Studies; History; Modern Languages and Cultures; Cross-Faculty Studies; and the School of Creative Arts, Performance and Visual Cultures, which
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Required Experience Background in weed ecology and weed management in agricultural systems. Proficiency with R statistical software. Experience developing interactive data visualization tools or web
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data and visual materials; d) Contextualizing the research within the framework of the “ID-Scapes: Building Identity” research project; e) Assisting with the organization of events and the
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of Computer Science at UNNC is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and
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Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing, transport, healthcare and others. Your Remuneration
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 2 months ago
, structural biology, computational biology or a related field, and experience in computational structural biology, protein structure modelling, AlphaFold/multimer-based analyses, statistics, data visualization
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, protein structure modelling, AlphaFold/multimer-based analyses, statistics, data visualization, and interdisciplinary work at the interface of proteomics, structures and machine learning. Track 2
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the Offer Description section Selection process Please you can find the information in the Offer Description section Website for additional job details https://www.ecum.uminho.pt/pt/Investigacao/Paginas
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learning (selected papers): VisualGPT: Data-efficient Image Captioning by Balancing Visual Input and Linguistic Knowledge from Pretraining, Jun Chen, Han Guo, Kai Yi, Boyang Li, Mohamed Elhoseiny, Arxiv