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of related start-ups. For more information about our Center, please visit our webpage: https://vanguard.um6p.ma/ Offer description: There are many systems of interest to scientists that are composed
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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of hybrid foundation model-graph neural network architectures for gene perturbation prediction, including the design and implementation of novel training strategies under experimental constraints, e.g
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they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling
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of immunoglobulin production shape the survival of normal and malignant plasma cells. Using in vitro plasma cell differentiation systems, mouse models (9), and advanced molecular and cellular technologies (10), we
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to identify metabolic response patterns and develop predictive models for personalized nutrition. Supervising master’s and/or doctoral students to a certain extent Possibility to engage in teaching at
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, prior distributions and posterior predictive checks, model comparison, programming in R (python/Matlab), implementations using R-packages rstan/JAGS and brms/STAN or equivalent interfaces. References
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mining challenges. The overarching objective of this project is to develop computational models that can predict how effectively glycine-based solutions extract precious metals from ore, enabling
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required for the project or the hosting universities. This full-time 3 year PhD studentship focuses on the use of technology to assess symptoms of PD and for PD prediction. The key aim of this PhD is to
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: Implementation and fine-tuning of antibody design models (RFdiffusion and boltzgen, AlphaFold3 etc.). Implementation of affinity prediction and maturation (FoldX, RosettaFold, ESM etc.), virtual screening and