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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
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Network ReDiLEEP (https://redileep.eu/ ). ReDiLEEP brings together leading universities, research institutes, and non-academic partners across Europe and beyond to advance response diversity research and
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an ecosystem. Our preliminary data suggests that this may be the case. If this hypothesis will be confirmed, it would mean that several independent baselines should be included in the isotope flux models, even
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translational model based on patient-derived tumour organoids that reproduce the realistic microanatomy of the tumour. These organoids will be used for translational testing of nanotherapeutic activity
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models that bridge the gap between laboratory settings and natural environments. It fits with Sustainable Transitions axe of the TIRIS program (https://anr.fr/ProjetIA-22-EXES-0015 ), addressing challenges
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into the electromagnetic model for robust performance analysis? Information Antenna and RF systems play a pivotal role in society by providing a crucial enabling medical diagnostics, transportation, and communication in
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modelling. References/further reading Wang, X. Q. et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature 621, 868-876 (2023). Danenberg, E. et al. Breast tumor
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. The PhD student will be in charge of analyzing the full data set in order to finalize the background model, study the two-neutrino double-beta decay of 82-Se, and search for neutrinoless modes. Where
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of interest, e.g. the spectral density of strongly correlated models, as measured in ARPES. • The mathematics of the approach will require a lot of innovative developments too. In the only published article