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Field
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: graph neural networks, natural language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance
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preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research results collected in accordance with the research protocols as stipulated. Prepare and present
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: Enrollment in a Master's or PhD program for Mathematics or related field Familiarity with math software/tools (e.g., MATLAB, graphing calculators, Microsoft Excel, R) Additional Information: This is a part
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using graphs, charts or tables to highlight the key points of the research results collected in accordance with the research protocols as stipulated. Proofread and edit research data and documents
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the PhD thesis in either language, English or German. Full-time / part-time full-time Mode of study Hybrid Programme duration 6 semesters Beginning Only for doctoral programmes: any time Additional
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PhD Position in Colloidal Assembly for Nanostructured Lithium-Ion Batteries Faculty: Faculty of Science Department: Department of Chemistry Hours per week: 36 to 40 Application deadline: 15
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The proposed PhD project aims to build a machine learning/deep learning-based decision support system that provides recommendations on precision medicine for paediatric brain cancer patients based
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trait-associated sequence variation. We offer a PhD position at the interface of computational and statistical genomics, and bioinformatics. Project background Cattle are an interesting «model organism
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(graphs, schema, structure models, etc.) to illustrate results of research. ● Communicate findings during regular group meetings. ● Help with writing, assembling, and editing manuscripts, grants and
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knowledge graphs and multimodal embeddings for cancer patient digital twin construction. Lead and co-author high-impact publications and grant proposals. Collaborate with clinicians, bioinformaticians, and