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Field
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computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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be also encouraged to explore other research opportunities or collaborations within the group. Tools and techniques to be developed include but are not limited to MR pulse sequences, machine learning
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the online application tool . Review of applications will begin immediately and continue until the position is filled. More information Lab website: https://demeulemeesterlab.sites.vib.be/ VIB Center
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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tools in research. Excellent written and oral communication skills, with a proven track record of publishing scientific papers and delivering presentations. Experience with machine learning techniques
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, funded by Kempe fundation is full-time for two years with access may 2026 or by agreement. Departmental specific information The research group led by Jonas von Hofsten (https://www.umu.se/en/staff/jonas
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website: https://www.ucd.ie/workatucd/jobs/ Where to apply Website https://www.aplitrak.com/?adid=eWFzZW1pbi5vemRlbWlyLjE5OTYwLjk5MDhAdW5pY2R1Ymxp… Requirements Research FieldEngineeringEducation LevelPhD
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Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data
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occurs via small-scale extreme events that propagate to large scale. A detailed check of this hypothesis thus requires multi scale tools and dedicated experimental setups as well as the development
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particle formation for atmospherically relevant molecules. ORCTOOL (Organic Cluster Tools) aims to create a toolbox for understanding and cost-effectively predicting the rate of massively multicomponent