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techniques: identifying the factors that establish early RT at target genes, determining how they promote translocation biogenesis, and testing them in preclinical models. The work combines CRISPR engineering
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to developing, designing and conducting research projects under general direction of the PI but in self-driven fashion; developing appropriate research methods; creative use of animal models; data analyses and
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, distributed control, formation control, perception, and decision-making in complex environments. Design and implement data-driven approaches, including machine learning, reinforcement learning, surrogate models
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on developing multi-scale mechanical models to predict how printed inks behave under mechanical and environmental stress. Your role: Build multi-scale models and extend the Eindhoven Glass Polymer Model for latex
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to use data and modelling to make historic buildings energy efficient – without compromising their cultural value? Join the research project DASHER at KTH. DASHER (Data-driven Structured Historic Energy
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David Levinson , the successful candidate will contribute to the development of hybrid quantum-classical modelling approaches that support improved analysis, simulation, optimisation, and decision making
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. For more information about the RNA Technologies Flagship, visit: https://rna.iit.it/ The project aims to develop a new generation of artificial intelligence models to systematically investigate the role
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touted our success in developing the technologies that took on acid rain in the 1970s and mercury in the early 2000s. Program Goals The NETL Postdoctoral Research Fellowship Program (Postdoc) is a high
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. Scientific Application & Validation Apply UXarray to real-world Earth science analysis workflows using outputs from high-resolution atmospheric, oceanic, and land surface models. Develop and publish Pythia
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methods for the modelling and causal analysis of mass transit systems. The research will focus in particular on the development and application of data science methods to address key challenges in capacity