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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is
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populations from New Guinea using museomic data Assembling high-quality reference genomes and generating whole-genome resequencing data of avian skins Inference of evolutionary history using Ancestral
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eye tracking, we will study how people coordinate and interact within these settings. The project is carried out in collaboration with partners at RWTH Aachen University and the University of Rennes
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. Bonus lectures can be picked by the students depending on their interests and project-specific requirements. Students can deepen their knowledge about selected topics (e.g. Bayesian Statistics, HMMs, AI
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research with numerical modelling. The group also has a strong track record in data-driven modelling of unsteady flows. This project explores how paired floating vertical-axis wind turbines can enable wind
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(causal inference and pathobiology). iii) Integrating knowledge of clinical implementation channels. Other tasks may also be assigned. Eligibility Students with basic eligibility for third-cycle studies
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). Footage will be collected using various underwater cameras deployed near the seabed. The sampling methodology is considered non-invasive because no fish is harmed, and the sampling infers almost
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We are seeking an enthusiastic and capable individual to join our team as a PhD researcher in developing instrumentation and simulations to monitor and track satellites. The successful candidate
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utilise numerical techniques including the finite element method to describe biofluid flow and deformation in the human brain tissue. Parameters are inferred from clinical data including medical images