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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
materials science or a related discipline • Some knowledge of the theory of materials and experience with computational methods in materials science • Some experience with machine-learning interatomic
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interactions among neighbouring agents and their environments. The research will exploit an interdisciplinary approach that combines control theory, nonlinear dynamical systems, robotics, and formal methods
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application”. When formalizing the application, if a classified document is submitted that reveals commercial or industrial secrets, or secrets relating to literary, artistic or scientific property
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from other maps. The ERC funded project GeoTrAnsQData project addresses this by developing a GeoQA method that converts questions into executable geo-analytical workflows, turning geodata into new answer
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, maps must be created or transformed from other maps. The ERC funded project GeoTrAnsQData project addresses this by developing a GeoQA method that converts questions into executable geo-analytical
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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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 to transform graphs
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candidate, you will develop methods that combine data-driven autonomy with formal safety guarantees and validate them in real time through simulation and experimental evaluation. The position is hosted
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related discipline • Some knowledge of the theory of materials and experience with computational methods in materials science • Some experience with machine-learning interatomic potentials • Good
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes