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temporal scales from seconds to hours and beyond. The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between
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learning to automatically build models from experimental data while directly embedding physical and mathematical knowledge within the learning architecture. This hybrid approach produces more reliable models
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transformations. The project investigates a hybrid approach that combines deep learning with grammatical inference to develop models that are interpretable, efficient, and mathematically verifiable while leveraging
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of shape modelling and contribute to attracting external funding. You will assist in the supervision of PhD students. Profile You hold a PhD in physics, mathematics, engineering or computer science from a
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student-centered university. The successful candidate will have a PhD in Mathematics, Physics or related field or extensive applicable experience and must be able to teach lab-based courses. The candidate
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or comparable with deep knowledge in continuum mechanics, structural analysis, advanced mathematics, modelling and simulation We are looking for first-class graduates with expertise in the RTG
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presentations to stakeholders 3. Contribute to funder reporting Qualifications Must have a PhD or equivalent in applied mathematics, statistics, biophysics, or similar. Must be able to undertake full-time
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Researcher (R1) Positions PhD Positions Application Deadline 17 Feb 2026 - 17:00 (Europe/London) Country United Kingdom Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
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Infrastructure? No Offer Description Work group: IAS-6 - Theoretical Neuroscience Area of research: PHD Thesis Job description: Your Job: This PhD project bridges between classical analytical methods and modern AI
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Graduate School https://www.visualintelligence.no/about/vigs Jarli & Jordan/ UiO via Unsplash Jarli & Jordan/ UiO What skills are important in this role? The Faculty of Mathematics and Natural Sciences has