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- Eindhoven University of Technology (TU/e); Published yesterday
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stakeholders in the Dutch battery ecosystem to develop and demonstrate the next-generation algorithms and models for the future Battery Management System. The PhD student will work on topics related to: Develop
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students to become experts in a specific domain of choice. This vacancy is explicitly targeted at candidates interested in algorithmic biases and developing methodological approaches to tackle this challenge
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1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD position 2 will focus on designing scalable
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bottlenecks in clinical radiology workflows through observations, structured workflow mapping, and close collaboration with clinical staff. Design, develop, and evaluate AI-based and automated workflow
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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Help revolutionize healthcare! Develop innovative technologies
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of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping the technologies that underpin a more sustainable and
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exploited by algorithms, leading to efficient solvability. Due to the development of such algorithms, structured integer programs play a critical role in many decision-making processes leading to improved
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for Mathematics and Computer Science (CWI). QuSoft’s mission is to develop new protocols, algorithms and applications that can be run on small to full-scale prototypes of a quantum computer. QuSoft has over 30 full
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participants of the Netherlands Twin Register, integrating genetic and psychological data where relevant. Beyond algorithm development, you will also address methodological challenges such as data quality, bias