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need to integrate ESG considerations into their decision-making processes, not just in risk selection, but also in pricing, underwriting, and portfolio optimization. Despite the growing relevance of ESG
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to join our world-leading research program in robotics, remote sensing, and data-driven approaches for sustainable agriculture. PhenoRob’s mission is to transform crop production by optimizing breeding and
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for Accelerated Materials Innovation, which aims to transform the discovery and optimization of high-performance functional materials through a fully integrated, interpretable AI platform. MAIAMI aims to establish
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processing), 3D spectro-microscopy imaging for electrode optimization, and full cell assembly with operando X-ray/Neutron studies for interpreting electrochemistry. Advancing the next generation of electrode
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optimization of Gene Editing vectors and their delivery to target specific loci in the human genome in collaboration with different world-renowned research laboratories specialized in rare diseases and oncology
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experience in molecular biological methods, microbiology and cell cultivationmethods, sterile work and, optimally, handling of complex communities. Understanding of sequencing-based microbiome analysis methods
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of multi-connectivity (MC) frameworks for multi-orbit satellite systems (e.g., GEO-MEO-LEO) Develop, optimize, and experimentally validate MC-based reliability solutions for multi-orbit systems compared
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on microfluidic and physical principles, fabricate & optimize using state-of-the-art microfabrication techniques and characterize chip performance (fluidics, mechanics, and reproducibility). Method development
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environmental conditions - Optimize material formulations for scalability and field deployment Candidate Requirements: We are seeking a highly motivated candidate with: - A background in civil engineering
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Your Job: The electrocatalytic interface engineering department, led by Prof. Dr.-Ing. Simon Thiele focuses on the manufacturing, analysis, and simulation of functional materials to find an optimal