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Field
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optimizations, creating endogeneity. Traditional discrete-choice and market share–based methods often fail under these constraints. Recent work has begun developing robust estimation frameworks that integrate
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marine sciences, biological oceanography, ecology, or computer sciences. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a
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Sciences (TSHD). DCC researchers explore cognitive and social aspects of human communication, through a multi-method approach, combining carefully designed experiments with survey methods, corpus analyses
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for sustainable mobility and the strategic placement of car sharing stations is crucial to maximize user adoption. Using causal effect estimation and spatially aware predictive methods, tools will be developed
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application! We are looking for a PhD student in AI and machine learning with a focus on generative machine learning methods for cyber security applications. Your work assignments The primary focus of this PhD
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10th November 2025 Languages English English English Do you want to develop methods in the interface between AI and forest ecosystems? PhD scholarship: methods for characterizing forest structure
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part will be devoted to the study of the cyclability of materials: it will aim to establish links between the nature of precursors (notably from recycling), synthesis methods, physical properties and
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to real-world error patterns by means of learning methods. This requires a recognition of the diverse and complex error patterns that can occur in quantum devices in real-world scenarios. To achieve
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, based at the Department of Computer and Information Science. These positions are funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP). Wallenberg AI, Autonomous Systems and Software
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work on developing improved methods using deep learning with 3D point clouds to characterize forest ecosystem structure and function. 3D point clouds from LiDAR and photogrammetry provide an excellent