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Field
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Challenge: Developing, operationalizing, quantifying, and embedding complex human and legal values into alignment pipelines for AI systems, open-weights, and foundation models. Change: Advancing
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3 Jul 2026 Job Information Organisation/Company UNIVERSITY OF HELSINKI Research Field Mathematics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Application Deadline 31
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a wild, non-model plant species. Your job To face climate change and other environmental challenges, the capacity for rapid adaptation is crucial for both natural plant populations and crops
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investigates the reproducibility of HP data processing pipelines using large language models (LLMs) to replicate published computational results. According to Starace et al. (2025), the state of the art in AI
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-generation multimodal foundation models for digital patient twins in oncology and cardiovascular medicine. The position is part of the EU Horizon Europe project TWIN-X, Digital Twins with Generative AI
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the PhD position. The topic of the PhD fellowship is at the interface of numerical mathematics, agentic and generative AI models, and computer science. A successful candidate will be offered a three-year
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Description The main tasks to be carried out by the selected candidate will be the following: ● Develop new methods for the uncertainty quantification of non-linear statistical models using the 'online
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Trondheim. The Department of Mathematical Sciences, NTNU, will host the PhD position. The topic of the PhD fellowship is at the interface of numerical mathematics, generative AI models, and computer
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statistical learning theory and probabilistic models; prior exposure to notions of robustness, resilience, or uncertainty quantification is an advantage. Mathematical maturity and experience with formal
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them for specific tasks. The project will combine: Mathematical modelling of dynamical systems; Computational photonics simulations; Comparison with real physical systems (especially photonic systems