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offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
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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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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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are looking for candidates who have experience with developing AI or machine learning models, as well as bacterial sequence analysis. You should be familiar with relevant programming languages such as Python
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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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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