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the next generation of miniaturized in vitro models to advance regenerative medicine. Your colleagues: A highly interdisciplinary team at MERLN, working within the national MDR consortium. The project Since
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to relate model structure to outcomes and interpret them in biologically meaningful ways. A collaborative, curious, and creative mindset. Fluency in English (written and spoken; minimally language level C1
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-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up
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twins and determination of the structural properties of rotor blades to improve the estimation of remaining useful lifetime (RUL) along with other requirements and simulations. Your work will advance
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, the REMOD-HEALING project will contribute to scientific advancement and innovation in wound healing and regenerative medicine through a coordinated, interdisciplinary effort, ultimately leading to societal
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new paradigm in the validation of autonomous driving software, focusing on the intersection of Large Language Models (LLMs) and Autonomy 2.0 / End-to-End (E2E) approaches. While E2E models promise
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model that explains lattice distortions and branching mechanisms. (4) Analyze experimental data using advanced computational tools and present results in research meetings and scientific publications
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language models and structural data. Build systems biology frameworks to characterize time-resolved protease network activity during tissue repair. Validate identified biomarkers through targeted proteomics
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mathematical modelling. Who are we looking for? We are looking for a candidate with a master training in biochemistry, biophysics or structural biology; keen interest in proteins and dynamic networks to be
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Materials Characterization; Biomaterials, Bioinspired and Self-Assembled Materials; Energy Materials and Sustainability; Materials for Structural Applications and Extreme Environments; Modeling, Theory and