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large language models (LLMs)—that is, the inability of a model to effectively process or understand visual information. This work involves integrating visual encoders with language models to create
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suited to overcoming climate change threats to natural and production forest systems, and identify the risks of, obstacles to, and opportunities for, integrating AM into governance frameworks. Most
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)—that is, the inability of a model to effectively process or understand visual information. This work involves integrating visual encoders with language models to create multimodal systems. The emphasis is
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: using time-series and comparative datasets to build dynamical models that link developmental processes to evolutionary outcomes. Predictability of evolution: creating integrative models that combine
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functionalities. The research aims to expand the capabilities of organic electronic devices by integrating light-responsive and multi-modal operation. The tasks will include: Exploring new doping strategies
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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-WISE NEST project. This position will be with the Division of Artificial Intelligence and Integrated Computer Systems (co-PI: Prof Fredrik Heintz). We will strive for a tight collaboration between the
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and Integrated Computer Systems (co-PI: Prof Fredrik Heintz). We will strive for a tight collaboration between the involved project participants, including regular meetings and setting up a joint
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that encompasses research units in Chemical Ecology, Resistance Biology and Integrated Plant Protection. Both applied and fundamental research are performed at the department, providing an excellent learning
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of the student is of a person fully committed to forest economics research with foundational training in research methods. The candidate will be responsible for: integrating economics and natural resource