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mathematical control theory, and a keen interest in machine learning to apply for the PhD position within the Dynamics and Control section at the Department of Mechanical Engineering, Eindhoven University
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repaired, reused, or discarded requires sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Would you like to work at the intersection of transportation, robotics and machine learning
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learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts. For example, we would like to be able
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Join us to decode how genetic variation reprograms brain cells and disrupts their communication using AI Job description We are looking for a PhD student to work at the intersection of machine
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts
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models using cutting-edge language technology. The project involves collaboration with experts from TU Delft, focusing on enhancing the security of machine learning model sharing without compromising data
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and machine learning. Master of Science (MSc) diploma in Transportation, Robotics, Computer Science, Logistics, Operations Research, Industrial Engineering, Applied Maths or any other related field