11 algorithm-sensor-"University-of-Gothenburg" Fellowship positions at University of Oslo in Norway
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) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain together. • Apply quality-diversity methods to discover a wide range of high-performing designs
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. • Integrate and test autonomy stacks (perception, learning, planning) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain together. • Apply quality-diversity
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of Oslo and the Norwegian Defence Research Establishment (FFI). The project aims to enhance current multi-sensor situational awareness systems integrating them with a new autonomous unmanned ground vehicle
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-sensor situational awareness systems integrating them with a new autonomous unmanned ground vehicle capable of navigating Norwegian forest environments. The main goal of the project is to develop and
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of oil spills in the ocean based on satellite imagery. A key focus will be to develop oil spill segmentation approach based on optical sensors, and how this can be integrated with SAR sensors, current
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role of secreted immune metabolites in these dynamics. The successful candidate will lead a project to develop novel sensors for intravital microscopy to study how these metabolites drive population
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lead a project to develop novel sensors for intravital microscopy to study how these metabolites drive population dynamics. The Jacobsen laboratory has a dedicated 2-photon microscope for this purpose
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the ocean based on satellite imagery. A key focus will be to develop oil spill segmentation approach based on optical sensors, and how this can be integrated with SAR sensors, current satellite imagery
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algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and neuroscience. The candidate is
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using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and