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Field
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globally having access to large (>10,000 patients) matched multimodal data across radiology, pathology and molecular profiling and clinical data. The focus of this position is on developing methodology
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! You will demonstrated expertise in developing machine-learning interatomic potentials (MLIPs) for large-scale molecular dynamics (MD) simulations of materials. Together, we will push the boundaries
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be done via computer simulations, including Monte Carlo and molecular dynamics, combined with the use of statistical mechanics to predict e.g. phase transitions, nucleation rates, etc. The work will be
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, we aim to generate knowledge towards the development of sustainable pest and disease management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can
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about the molecular basis underlying variation in these traits. Atlantic salmon is among the most variable vertebrates on Earth in terms of life histories, making it a powerful model to study how complex
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-handed one, known as enantiomers. Their handedness greatly influences molecular interactions, sometimes making the difference between a medical drug and a toxic substance. Therefore, methods for detecting
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modern applications. Their unique properties make them ideal quantum systems ideal for benchmarking state of the art theories in atomic and molecular physics. The EU-funded Horizon Europe Doctoral Network
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, to industrial catalysis and green energy production. This PhD project offers a rare opportunity to explore hydrogen surface collisions at a fundamental, molecular level to gain unprecedented insight into the role
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management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can meet the needs of current and evolving plant production systems. Read more about our
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tools and simulation models to (1) detect novel pathogens early through broad genomic screening, (2) support hospitals in mitigating the impact of pandemics through optimized data-driven decision-making