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Field
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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We are inviting applications for a fully funded 3.5-year PhD Computer Science studentship at the University of Warwick, jointly supported by GlaxoSmithKline (GSK), to work on an ambitious project
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PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and
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methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using methods you develop before being transferred to a knowledge graph
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writing for faculty and researchers. Support the preparation of institutional scientific documents, templates, and standardized text for research proposals. Your qualifications should include: PhD in
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) offers two positions as Research Associate / PhD Student (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting as soon as possible
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is mandatory Stipend 3: Learning the Structure and Dynamics of Complex Networks We seek a PhD candidate to develop novel representation learning methods on graphs for modeling temporal networks, with
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, or the misinterpretation of some inputs to result in a particular behaviour that is favourable to the attacker. In this thesis, the PhD candidate will first study the impact of decentralizing ML algorithms