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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description he project aims to develop a data-driven model to
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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generation and predictive modeling by measuring the conductivity and permittivity of diverse electrolytes. The research will be structured into four key phases: (i) the design, fabrication, and validation
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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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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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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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 7 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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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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to develop an aeromedical dispatch management software as a technology hub that provides data-driven prediction model and an automated dynamic decision model. The successful candidate will be responsible