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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
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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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data Design algorithms for correlating low-level events into process-level attack models Contribute to joint framework development with TU/e on continual learning Collaborate with industry partners
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industrial processes. Your research will drive a paradigm shift in how TES systems are modelled, integrated, and controlled within industrial settings. You will develop novel, adaptive, physics-informed models
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are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response to climate change. Engineering and applied physics
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Job Description The project takes place in the Quantum Light Sources group at DTU Electro, where we design, model, fabricate and test sources of single photons or entangled photon pairs
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Analytics. The core focus of the PhD project will be to develop and test planning and optimization models to analyze new and innovative Hospital-at-Home systems to improve access to healthcare for elderly and
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cement based on literature, theory, and experiments. Optimization of composition with other waste materials. Thermodynamic modelling and experiments with advanced technologies are used. Development of a
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and colleagues working with theory that will complement your work with density functional theory, phase-field simulations, and finite element modelling. Qualified applicants must have: Enthusiasm
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and Northeastern University, USA. Responsibilities The PhD project involves developing a flexible vegetation model within the OpenFOAM platform, where vegetation stems are represented as nonlinear