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help design strategies that are both evidence-based and publicly accessible, bridging the gap between complex scientific knowledge and societal decision-making. Key aspects include: Applying AI-based
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simulation, stakeholder mapping, and scenario analysis. The project is led by Professor Frank Dignum (main supervisor) and Dr. Jason Tucker. Requirements The general admission requirements for doctoral studies
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mapping, and scenario analysis. The project is led by Professor Frank Dignum (main supervisor) and Dr. Jason Tucker. Requirements The general admission requirements for doctoral studies are a second- cycle
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EU-MSCA PhD position: Molecularly imprinted polymers for phosphopeptide assays of oncogenic pathways
Good knowledge and interest in chemistry laboratory research Experience in organic chemistry such as synthesis, purification and analysis Interest in and ability to learn new techniques Ability to work
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experience in standard biochemical analysis methods, advanced molecular cloning techniques, CRISPR/Cas9 and experience in culturing and transfection of eukaryotic parasites. Experience in light microscopy
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enrichment techniques combined with MS/MS methods and data analysis have revealed a large extent of PTMs in proteins a lack of efficient affinity-based enrichment techniques causes several of the modifications
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properties and processes, as well as how soil functions are affected by changes in environmental conditions, including climate change. Through research, environmental analysis and education, we contribute
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environmental conditions, including climate change. Through research, environmental analysis and education, we contribute knowledge about future sustainable land use and develop new solutions as a basis for
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and computer science, connected to MDU’s existing research areas. The PhD project focuses on the development of a large language model (LLM)-based AI agent specialized in energy decision-making
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science, connected to MDU’s existing research areas. The PhD project focuses on the development of a large language model (LLM)-based AI agent specialized in energy decision-making, including: development of AI models