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Is the Job related to staff position within a Research Infrastructure? No Offer Description Computational geometry is the area within algorithms research dealing with the design and analysis
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linearization with limited or imperfect models. Learning-enabled control dynamics Embedding optimization and learning algorithms (e.g., SGD, Bayesian updates) into control design and analysis. Attack-tolerant
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May 2026 Apply now Are algorithms neutral tools, or do they actively shape the world they model? In this PhD, you will bridge the gap between building and critically studying Human-Centred AI systems
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this postdoc position, the focus is on methods and algorithms for large-scale graph analytics, in particular network science approaches for analyzing longitudinal, population-scale relational data derived from
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a focus. Traditionally, this is done through iterative algorithms (‘trial and error’). In this project, we aim to develop a radically different approach where the correct shape is computed using a 3-D
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(LES) results. Key Responsibilities: Develop and refine numerical algorithms for real-time wind field forecasting. Validate forecasting models against high-fidelity LES data and field measurements
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system is expected to have, (ii) set up the connection with a software system for executing tests consisting of inputs and outputs, and (iii) select test generation algorithms that derive tests from a
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algorithms to shape the liveable cities of tomorrow? Job description Human-centred AI techniques, such as Reinforcement Learning from Human Feedback (RLHF), hold great potential for supporting design
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probabilistic generative models for networks; analyze real network data from different application domains; design efficient algorithmic implementations of the theoretical models. You will be supervised by Dr
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of platform data handling and payload data processing equipment; the implementation, inference, verification and validation of algorithms** on data processing hardware platforms for space applications** in