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Job Description Do you want to be part of a team that is developing novel tools to create genetic medicines and better model systems for testing them? Then join the Precision Medicine Technologies
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scalable optimization models that capture the sparse structure of water networks. The proposed research will develop methodologies and advanced solutions that will help societies improve energy efficiency
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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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optimization frameworks that adopt an interdisciplinary approach, integrating concepts from operations research, transport modeling, welfare economics, transport justice and machine learning. You will be based
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experimental work and risk modeling, you will help uncover how chemicals and microplastics are released from consumer products and contribute to the development of Safe and Sustainable by Design (SSbD
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, what motivates them to engage with disruptive technologies, and how emerging regulatory frameworks and business models influence their decisions. The doctoral research will focus on mapping the diffusion
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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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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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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