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models to detect food safety compliance risks Integrate regulatory, environmental, and microbial data from food SMEs Design user-friendly decision support systems for inspectors and producers Co-create and
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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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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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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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to circularity and sustainability in the footwear industry. Through advanced experimental work and modeling, you will help uncover how the composition of shoes will affect the circularity potential, and advice
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of the Marie Skłodowska-Curie Doctoral Network SCARPA, a European training network committed to circularity and sustainability in the footwear industry. Through advanced experimental work and modeling
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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