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topic of transport geography.More specifically, you will work on the topic of "inclusive, sustainable, and efficient accessibility: systematically evaluating and learning from 'smart' initiatives." What
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of the future. We work for and with society. Our motto is: we are making places better together . If you would like to learn more, visit rug.nl/frw . The Department of Economic Geography, in which the position
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learning models (e.g., multimodal AI, large language/world models) with specific finetuning for ELEVATE; designing geographically context-sensitive urban design recommendations that promote active mobility
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, long development times, and the risk of toxicity against healthy tissue. At the heart of these challenges lies the TCR specificity problem: understanding how T-cell receptors (TCRs) recognize peptide
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and high-speed microscopy with AI and machine learning to form stable liposomes from libraries of (novel) phospholipids that can robustly encapsulate cell-free gene expression systems. You will then
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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understand the inner workings of cells at the molecular level. The group houses an excellent infrastructure that includes more than a dozen state-of-the-art mass spectrometers, combined with cell culture
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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understand the inner workings of cells at the molecular level. The group houses an excellent infrastructure that includes more than a dozen state-of-the-art mass spectrometers, combined with cell culture
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workshops and reflection sessions, contributing to collaborative and transdiciplinary knowledge development under the principle of “learning together, developing together"; Publish articles in both peer