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Job Description We invite applications for a 3-year PhD scholarship at DTU Energy. The project will integrate innovative physics-based atomistic modeling methods and data-driven inverse molecular
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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friendly catalysts and substrates. We use NMR spectroscopy for serendipitous discoveries and unbiased characterizations of molecules, their conversion, and their interactions in complex systems. Solvent
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performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators (e.g., Kalman Filter
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of the nonlinear structural performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators
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two-dimensional active sites, however, have a fundamentally limited efficiency for facilitating complex reactions that involve three or more reaction intermediates, due to the "scaling relations". In
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and
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-enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your
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pharmacology. The PhD project will focus on testing and optimizing antisense oligonucleotides in preclinical in vitro models, as well as formulating these molecules into a novel biodegradable delivery system