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, inspiring students in the classroom, or helping to shape everything that makes our education and research possible. PhD Candidate in MIP-Based Sensor Engineering for Antimicrobial Resistance Detection Our
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occurred, exposing the limitations of current detection timelines. This reactive posture is worsened by a visibility gap in the DNS ecosystem. A lack of transparency in registration data, coupled with
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Vacancies PhD position on Real-Time Detection of DNS Abuse, from Reactive to Proactive Key takeaways Malicious actors increasingly abuse the Domain Name System (DNS) by registering new domains
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of these are highly localized. Localized corrosion under a coating is however typically difficult to detect visually. Electrochemical Noise (EN) can detect this at an early stage and is not limited by geometric
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Infrastructure? No Offer Description Develop machine learning models to detect early signs of abrupt shift towards clean energy technologies and make climate action adaptive to this information. Job description
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Develop machine learning models to detect early signs of abrupt shift towards clean energy technologies and make climate action adaptive to this information. Job description Positive tipping points
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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