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desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS and R is a merit. Proven excellence in written and spoken English is essential. The fieldwork will
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multimodal systems. The emphasis is on agentic approaches, where an LLM interacts with visual tools, which may themselves be neural networks. Central challenges include enabling LLMs to reason about visual
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on agentic approaches, where an LLM interacts with visual tools, which may themselves be neural networks. Central challenges include enabling LLMs to reason about visual structures, designing
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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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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