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domain tools (RDKit, molecular graph ML, ELN/LIMS APIs, instrument drivers) to build composite agents that plan, simulate, and execute DMTA tasks Prototype and iterate rapidly on agent planning strategies
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to students pursuing degrees through the doctoral level. More than 20 percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory
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Applications: Not Applicable Required Other Computer Applications: Required Additional Knowledge, Skills and Abilities: 1. Ability to prepare for and collect data. 2. Ability to enter data and update graphs
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. Collaborative and collegial, demonstrates integrity Organized, able to maintain and coordinate multiple items. Excellent computer skills; proficient in data entry, analysis, graphing, Microsoft Office Familiarity
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Graph Machine Learning and Graph Data Management At Section
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the department is available at: https://www.umu.se/en/department-of-computing-science/ Project description Graph transformation is a well-established theory that studies computational methods
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an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning
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preparation for analysis; use spreadsheets and databases to develop and maintain records and create reports — 10% Prepare and present summary narrative reports, PowerPoints, graphs, tables, charts, and
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% Support activities related to fungal culture and inoculum preparation. 10% Assist with preparation of graphs, tables, PowerPoint slides, and posters for extension and scientific meetings. Qualifications
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maps. Knowledge graphs can be used to model these transformations and to link geodata sources to questions. In this project we will apply symbolic and sub-symbolic AI methods to scale this up across