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regions of the world, and at the same time impact the climate positively utilizing CO2 as raw material. To be launched into scaled solutions, the technology needs to be optimized through leveraging digital
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Department (DRIS), you will participate in research activities on the optimization of non-Newtonian fluid injection for the decontamination of polluted soils. Tests will be conducted, in 1D columns, in 2D
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and mRNA translation. The successful candidate will establish live imaging tools to analyse translation dynamics in regenerating axons, using an ex vivo culture model previously optimized (Schaeffer et
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). The ideal candidate will have: A PhD in environmental science or closely related discipline by the start date of the appointment Broad understanding of eco-evolutionary optimality concepts and modelling
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sensor data, with applications in disease modeling and the development of material science-based innovations. These efforts aim to optimize system performance and uncover novel biological insights in close
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, modelling, optimization and validation, and focus on: Develop thermally integrated storage and conversion systems, including Carnot batteries and/or high-temperature heat pumps based on power cycles. Design
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fertility, optimize nutrient availability, and contribute to more sustainable agricultural practices. Job Responsibilities Study the biology, ecology, and physiology of microalgae and cyanobacteria
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the areas of Artificial Intelligence (AI) for materials science, with an emphasis on structure-property-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates
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are looking for a curious and driven postdoctoral researcher to join a project focused on improving how we study and optimize medical treatments. The work centers on advancing a vessel-on-a-chip platform—a
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our pilot cases Development of building simulation models supporting energy and indoor climate optimization Analysis of building performance data for occupancy detection and predictive modelling