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planning -Semantic-based Exploration -Source localization -Perception in sensor-degraded environments: -Localization in smoke and dust filled environments -Scene awareness -Biometric/triage evaluations, etc
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in real machines used in mining, forestry, construction, or the space industry. The doctoral candidate position is fully funded by the Marie Skłodowska-Curie Doctoral Network ENGAGE, which stands
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for networking, and access to robust administrative and technical services—all within a setting that offers attractive employment conditions. To learn more about the department, please visit: https://www.umu.se/en
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in real machines used in mining, forestry, construction, or the space industry. The doctoral candidate position is fully funded by the Marie Skłodowska-Curie Doctoral Network ENGAGE, which stands
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on behavioural syndromes and social networks in dogs and to some extent wolves. The selected PhD student will work with large-scale behavioural data sets using a range of approaches, including heritability
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diverse community of individuals from a wide range of nationalities. As a PhD student with us, you benefit from comprehensive career development support, opportunities for networking, and access to robust
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behavioural phenotypes and social systems develop and evolve. Specifically, the project will focus on behavioural syndromes and social networks in dogs and to some extent wolves. The selected PhD student will
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will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School
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networks (CNNs), which identify local correlations in the images. However, in this project, the aim is to go beyond standard CNN-based methods by developing new approaches based on transformers, and implicit
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, where models learn to restore images using only the noisy data itself — without requiring clean references. Existing approaches often rely on convolutional neural networks (CNNs), which identify local