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Project descriptionAutonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents
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into AI-driven conversational agents in public education settings, this project will explore how spatial positioning, movement, and embodied presence influence visitor engagement and knowledge retention
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topographic indices as environmental variables for mapping, and satellite data for weather. The doctoral student will be part of a broad research group with expertise in GIS, AI, soil science, forest ecology
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robots -Distributed task planning for collaborative missions -Behaviour tree based multi agent collaboration -Reactive task allocation in large scale missions For further information about a specific
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forests are merits. Skills in planning, executing, and reporting scientific studies, as well as experience with statistical analyses, GIS and literature reviews (incl. meta-analyses) are meriting
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basic understanding of, and a strong interest in, one of the following topics: Logic-based reasoning approaches, for example formal argumentation, or Formal aspects of autonomous agents and multi-agent
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Information Systems (GIS), programming in Python, practical forestry, nature conservation, cultural heritage management, as well as a driver’s license, are considered assets. Place of work: Umeå Forms
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biotechnology solutions based on scientific breakthroughs. www.SweTree.com Spray-induced gene silencing for control of damage agents SIGS (spray-induced gene silencing) is a promising biologically-based
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silviculture or ecological surveys, ability to work independently in the field, skills in GIS and R-statistical analysis, and good communications skills in written English. A drivers license is a necessity for
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, the random dropout of participating agents, and uneven distribution of data across agents. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part