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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous
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, calibration and reliability of large pre-trained models Probabilistic generative models and world models Probabilistic machine learning for scientific discovery Don’t see your exact idea listed? We encourage
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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model organisms, their application in conifers remains limited due to challenges associated with tissue structure, nuclei isolation and sensitivity to inhibitory compounds. This project aims to develop
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identity and extracellular signaling, but how cell types, signaling mechanisms, and transcription factors jointly determine tissue structure is incompletely understood. The Koplev lab is recruiting
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external large-scale datasets. The role focuses on establishing the data foundations for the program’s initial modelling efforts by identifying, evaluating, integrating, and structuring large biological
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leading the investigation of structural and biophysical properties of miniaturized tumor environment models. A multidisciplinary approach is expected, integrating microfabrication, cell component and