The candidate, who will join the Chemometrics for Environmental Omics group, will work on data analysis, leveraging the expertise of the research group to uncover meaningful patterns and insights from complex data sets, including patent descriptions and chemical, environmental, and economic information.
This project, titled “Artificial Intelligence Driven Innovations for a Sustainable Future by Enhancing Water and Air Quality”, addresses the global crisis of water and air pollution by leveraging advanced AI tools to aggregate and analyse scientific and innovation data, including over 120 million global patents and environmental databases. By employing natural language processing (NLP) and machine learning techniques, it aims to predict future demand for green technologies and enhance innovators’ ability to create sustainable solutions. One of the key factors is the economic evaluation of patent performance, crucial for guiding strategic decision-making in environmental innovation. The project will culminate in a web platform featuring AI-driven decision support tools, empowering innovators with predictive capabilities crucial for developing competitive and breakthrough green technologies.
Deadline: 1 August 2024
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