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agents, and their effects on particle morphology and filtration performance, providing opportunities to address more complex mechanistic questions. The duties may also include (e.g.) Research within
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. Analysis covers preprocessing, assembly of DNA fragments into complete genomes, imputation of missing data, filtering of bad data, prediction of the meaning of the DNA in individual cells, compression
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). This project will employ cell models with a thick glycocalyx as well as molecularly defined molecularmodels of the glycocalyx. You will establish a pipeline for single-particle tracking of viruses in three
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, generative diffusion models, flow models, optimal transport, stochastic filtering, sequential Monte Carlo, Markov chain Monte Carlo, and Bayesian inference and inverse problems is strongly advantageous. Your
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algorithms for resource-efficient learning, for example via data selection and filtering (leveraging that not all data is equally informative). You will also investigate complementary approaches that reduce
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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
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across forest ecosystems affected by intensive forestry. Leveraging a globally unique 60-year archive of weekly air filter samples from Kiruna and newly collected samples from Skåne, the PhD student will