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-edge interdisciplinary project aims to understand charge transport in the natural mineral feldspar, unlocking new ways of measuring the rates of Earth surface processes — from weathering and erosion
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-polymers using AI-driven process intensification, safe-and-sustainable-by-design principles, and smart polymer formulation. The project brings together leading academic and industrial partners to create a
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small-scale processing sector. By joining this project, you will contribute to the development of AI-powered tools that predict non-compliance, improve food safety monitoring, and ultimately protect
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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effective enzymatic recycling processes. We are looking for candidates with strong qualifications in some of the following areas, and a motivation to develop within others: Protein chemistry Enzyme kinetics
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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the monomers are reversible, making these polymer materials adaptive, healable, easy to process and recyclable. In this project, you will explore new types of stimuli-responsive supramolecular polymers
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bioinformatics, AI and ML software tools to integrate and process the datasets quickly and efficiently. You will also work closely with other computational and experimental biologists to uncover new insights
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Grant LUMIN. This cutting-edge interdisciplinary project aims to understand charge transport in the natural mineral feldspar, unlocking new ways of measuring the rates of Earth surface processes — from
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strong guidance from academic supervisors as well as from industrial experts. Responsibilities and qualifications Polishing is one of the last steps of the manufacturing process chain for industrial tools