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the positive ones for different stakeholder groups, as a basis for policy making? Are you interested in spatial optimization algorithms and uncertainty assessment? Then this PhD position at the Department
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to evaluate and advance machine learning algorithms for one of the following application areas: “Characterising forests variations in relation to distance from pre-Columbian earthworks in the Amazon forest
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an interdisciplinary team that works on cutting-edge questions ranging from mathematics and theoretical physics all the way to numerical simulation algorithms? Then apply now to join our team of researchers in
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algorithms, validated in real-time simulations and experimentally in collaboration with industry. The project: This project looks at the development of electromechanical friction wheel braking (EMB) systems
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algorithms. Vision Language Model (VLM) experience is desirable. Qualifications A high-grade undergraduate degree (first class or upper second) in computer science or MSc in related field. Skills Knowledge
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comprises a diverse and vibrant group of laboratories, with research interests ranging from environmental biology to biochemistry. The genetics, evolutionary biology and microbiome communities are strong
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of posterior curvature. The project will establish optimised OCT acquisition and de-warping methods, build robust segmentation and curvature-analysis algorithms, and validate clinically meaningful shape metrics
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on how genome merging alters gene expression, subgenome contributions, and epigenetic regulation over evolutionary time and under stress conditions. You will perform controlled glasshouse experiments with
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algorithms, and some knowledge of data science and machine learning (through coursework, self-learning, or personal projects). The selected student will work with Ph.D. and master's students to help develop
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and algorithmic framework to assess and improve the resilience of FL-enabled autonomous systems under such heterogeneity, explicitly incorporating the human in the loop. The project will draw