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- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Eindhoven University of Technology (TU/e); Published yesterday
- University Medical Center Utrecht (UMC Utrecht)
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18 Dec 2025 Job Information Organisation/Company University of Twente (UT) Research Field Computer science Mathematics » Algorithms Mathematics » Discrete mathematics Mathematics » Mathematical
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. Your duties and responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with
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). Information Key Responsibilities: Develop a generalizable and explainable (gray-box) model for adaptive patient monitoring. Utilize a mixed approach combining real and synthetic data for algorithm development
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learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g
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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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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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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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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