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integrates spatio-temporal analyses (including synthetic descriptions such as distribution envelopes, size structures, and joint species distribution modeling), trophic modeling, and machine learning
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Washington, D.C. Connections working at Johns Hopkins University More Jobs from This Employer https://main.hercjobs.org/jobs/22103428/modeler-x2f-data-scientist-i-x28-epidemiology-x29 Return to Search Results
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: Computational, Quantitative, and Predictive Modeling of Root Systems. This position emphasizes integration of phenomics and other -omics data into predictive frameworks. Research areas may include: Structural
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language model (LLM) methods to unlock information from Dutch electronic health record (EHR) free text for secondary use in research. Electronic health records contain a wealth of relevant patient
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for relevant separations such as CO₂/N₂ or CO₂/H₂. The thermodynamic study may be complemented by adsorption microcalorimetry measurements. Molecular modeling will be used to interpret experimental results
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, visit https://www.biocean5d.org/ . The applicants will work on close collaboration with Jose M. Montoya, from CNRS. - Developing analytical theory and/or simulation models on the relative importance
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biochemical datasets. A major focus will be on introducing new AI models to chart the chemical “dark matter” of the mammalian metabolome; examples of such models include large supervised or self-supervised AI
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. These triggers can be injected into the training dataset or directly into the model weights. These are then called poisoned. Due to parameter-efficient fine-tuning methods, backdoor attacks on large language
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Key Responsibilities: Develop and implement high-fidelity CFD and FEA simulation workflows for modelling heat
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formal methods. The successful candidate will contribute to advancing data-driven modeling techniques that enable formal safety guarantees for complex dynamical systems such as autonomous vehicles