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profiling of patient samples is essential to predict responses, identify candidate biomarkers and personalise therapy aimed at harnessing the immune system to target the tumour. This is a challenging
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geometries and process-induced defects demand new inspection approaches. The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop
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University College of Medicine, our goal is to use the lens of metabolism to better understand and predict cancer progression. We use a combination of experimental and clinical data paired with computational
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highly motivated PhD student to develop advanced models for predicting the fatigue life of additively manufactured steel in nuclear reactor water environments. The project focuses on modeling corrosion
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for predictive modeling scenarios, causal modeling is also within the scope of the position. The position is embedded in the ten-year gravitation grant Stress in Action, funded through NWO (Dutch National Science
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- specific predictive models, the lack of explainability in AI-driven decision processes, and the difficulty of capturing long-term dependencies in time-series data. In this project, you will focus
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of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real-time data acquisition. You will
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. The long-standing solar convective conundrum is the mismatch between convective flows inferred from helioseismology and flows predicted by state-of-the-art simulations. ReCon² addresses this by advancing
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topics such as statistics, high performance programming, machine learning and using data to constrain cosmological models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
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the following research areas providing a template for relevant directions: - Embodied Intelligence for Soft Robotic Systems - Foundational Models for Adaptive Soft Robots - Real-Time Adaptive and Stiffness-Aware