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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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project between the Department of Technology Systems at the University of Oslo and the Norwegian Defence Research Establishment (FFI). The project aims to enhance current multi-sensor situational awareness
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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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sensors for intravital microscopy to study how these metabolites drive population dynamics. The Jacobsen laboratory has a dedicated 2-photon microscope for this purpose. The candidate will have access
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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
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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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in programming language theory, algorithms, distributed systems and logic Experience with language-based techniques for information-flow analysis or access control, formal methods or semantic