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batteries at the molecular level. Novel spectroscopic approaches are developed and applied to the characterization of materials under working conditions (operando/transient approach). Relationships between
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response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design platforms. Furthermore, REUNATECH
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
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within fusion reactors, especially plasma-facing materials (PFMs) exposed to intense heat fluxes and energetic particles. Understanding and predicting how these materials degrade under such conditions is
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the change! We offer ideal conditions for you to complete your doctoral degree: Competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling
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features from unlabeled high-resolution microscopy data Training and evaluating segmentation models for detecting and characterizing defects such as dislocations Applying generative models (e.g., GANs
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and scalar fluxes across the air-sea interface is crucial for a number of environmental challenges, including weather, climate and sea state forecasting. The Air-Sea Fluxes group at the Institute
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focus on synthetic biology, biochemistry and/or chemistry. • Practical experience in protein engineering (structural and sequence design), bacterial production (S1 lab conditions, E. coli), protein
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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
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conditions. Environmental effects on electronics are an important area today due to the widespread use of electronics such as electrification of vehicles and use in connection with renewable energy systems