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into the psychological factors that impair consumers' ability to detect such deceptive claims. The project will develop and test a Washing Detection Model to better understand when and why consumers are vulnerable
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. These washing practices successfully deceive consumers at the cost of health and sustainability. You will delve into the psychological factors that impair consumers' ability to detect such deceptive
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smart industry. You will be part of a large national ‘Perspectief’ program Foundation Models for Industry (FIND), collaborating with leading Dutch universities, knowledge institutes, and industry partners
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Foundation Models for Industry (FIND), collaborating with leading Dutch universities, knowledge institutes, and industry partners. The FIND project Foundation for Industry (FIND) – Large AI Models for a
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’ program Foundation Models for Industry (FIND), collaborating with leading Dutch universities, knowledge institutes, and industry partners. The FIND project Foundation for Industry (FIND) – Large AI Models
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of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse Wave Scattering’. Inverse wave
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of the Department of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse
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the next. Your models will first be used to analyze completed experiments and identify trends, and later integrated into active learning and Bayesian optimization frameworks to suggest which experiments
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varying material properties. The resulting response will be analyzed using techniques such as Monte Carlo simulations. Identifying the variability of the model parameters using Bayesian inference
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chemistry concepts (desirable). Familiarity with chemical or biological databases (e.g., ChEMBL, PubChem, PDB) is a plus. Experience with Bayesian modelling, transfer learning, few-shot learning, or other