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. The post holder will have the opportunity to be involved in cutting-edge bespoke neuroimaging technology [3T/7TfMRI-EEG fusion] and advanced data analytics to uncover and predict patterns in large multimodal
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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physical agent-based models, as well as the integrations of omic information to validate model predictions and developed in the context of the HPC environments at the BSC and at other HPC centres in Europe
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model biases, and identify sources of predictability. The project will involve; 1) rigorous interrogation of NOAA GFDL's CM4X simulation output with respect to coastal sea level variability and relevant
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predictive models for drug response. Furthermore, we work on creating new treatment stratification methods to personalize treatment for individual patients. More information about the lab can be found here
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SDLs to synthesize and characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine
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and implement multimodal retrieval with re-rankers for robust profile selection. Design and train advanced AI models for digital twin: 3D model learning, prediction models from imaging and molecular
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refines algorithms and workflows for crop and pasture monitoring, modeling, prediction, and decision support and automation; Supervises graduate research assistants and student interns working
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Distributed, robust and adaptive model predictive control (MPC) School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline: Applications
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), multimodal vision and language models, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate