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from observations, sensors, or eDNA, in combination with environmental drivers, land-use history, and management. Experience with large and heterogeneous datasets is important. The successful candidate
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: Collaborative Localization and Sensor Integration This PhD position will focus on developing and integrating methods for collaborative localization and sensor fusion in the ABBA USV system. The goal is to enable
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include: Application (cover letter) Vision for teaching and research for the tenure track period CV including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching
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about DTU Electro at www.electro.dtu.dk . For more specific information on the Quantum Light Sources group, see also https://electro.dtu.dk/research/research-areas/nanophotonics/quantum-light-sources
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community data on plants or invertebrates derived from observations, sensors, or eDNA, in combination with environmental drivers, land-use history, and management. Experience with large and heterogeneous
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. The primary responsibilities and tasks are: Conduct research in robust positioning methods utilizing GNSS with emphasis on signal- and data processing algorithms and fusion with other sensors with emphasis
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sensors (in collaboration with sensor developers, local water utilities and authorities) Interact with stakeholders and end-users in co-creation workshops aiming to identify their monitoring and modelling
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., camera traps, thermal imaging, acoustic sensors) Practical skills in programming and analysis of large datasets Publication record in relevant areas Ability to communicate effectively in English, both
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with Danish and international industrial partners. More information about the AI RF Sensors group is available at: https://www.es.aau.dk/research/ai-rf-sensors Qualification requirements Appointment as
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including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) Representative