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Field
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degree in applied numerical mathematics, computational/theoretical physics, theoretical biology, computer science, or a related discipline; Written and oral proficiency in English, strong scientific
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, and stay abreast of the latest advancements in OLED display technology. He/she will oversee R&D activities related to OLED emitters and devices, providing technical guidance and leadership to optimize
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with advanced photoreactors, modular LED light sources, inline analytics, and machine-learning algorithms for the autonomous optimization of photocatalytic reactions. Research will address key challenges
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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. These structures are able to control numerous biological functions from sensing messenger compounds to dictating whether genes are switched on or off. This project will focus in particular on G-quadruplexes, four
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, you will develop analytical and numerical models describing the quantum dynamics of mechanical systems and their interactions with complex environments. Building on these models, you will investigate
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, by that enabling improved control and optimization. Stall detection will be a natural part. The PhD project is internally financed but will be associated to two large research programmes at NTNU and
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, linear algebra, probability theory, (Bayesian) statistics, optimization and elementary graph theory Familiar with machine learning and deep learning Programming experience (Python or Julia) and their
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brings together expertise in energy informatics, optimization, data science, social sciences, and governance to develop trusted data-sharing solutions for the heat transition. Within the project, you will
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studied intensively because of their importance in many natural phenomena and use in numerous applications. Embarking on a groundbreaking PhD journey, this research endeavours to revolutionize the landscape