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Arctic environments such as Greenland, where the flights take place in severe cold. You will work on sensor systems that withstand the arctic cold and, on the localisation, mapping and mission
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, computational biology, numerical analysis of partial differential equations (including ice and ocean dynamics), computational statistics and machine learning, as well as algorithm design and discrete
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, printed, bio-, and soft electronics. The present position is part of the Swedish Research Council (VR)-funded project “Biowaste-Based Stretchable Sensor Modules for Sustainable Plant Wearables
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comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures ( https://CGRlab.github.io/research/ ). About the research project We are open
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much of their signal. Radar and thermal cameras are less affected but give sparser or noisier data. Reliable localisation therefore needs several sensor types and a good understanding of how each of
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- Control of Communication networks - Markovian Processes - Network Based Localisation / Radio based connectivity - Adaptive bandwidth - Mesh networking - Wireless Sensor Networks - Edge Computing
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-based Exploration - Source localization - Perception in sensor-degraded environments: - Localization in smoke and dust filled environments - Scene awareness - Biometric/triage evaluations, etc. Mission
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design concepts for fluid batteries and develop tailored fabrications methods based on printing to realize and evaluate the concepts. The developed batteries will be integrated into wearable sensor
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, hydraulics/hydrology, thermodynamics (e.g. heat transfer processes) - experience of sensor-based monitoring, field sampling, machine learning, programming as well as working with large environmental