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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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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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. 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 computing resources and collaborates to address
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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