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numerical simulations to reproduce and predict magnetically confined fusion plasma experiments 2.Development of transport models based on simulation data and their implementation into integrated transport
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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positions at UCD working closely with industry partners, specifically LaNua Medical (https://www.lanuamedical.com/ ) and Integer Holdings Corporation (https://www.integer.net/ ). The project focuses on LaNua
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, skills, and experience in translating complex business needs into technical solutions using advanced analytics, including predictive modeling and statistical analysis, to drive institutional decision
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protein structural insight with hands‑on ML development: adapting and applying state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational
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(SHM), physics-based modeling, and data-driven analytics to enable predictive, performance-based decision-making and improve infrastructure safety, resilience, and lifecycle performance. The candidate is
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breed x system interactions. Including e.g. milk-based parameters according to other WPs, production system specific early prediction models for the control of endoparasites will be developed
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
projects are the analysis of gene expression patterns in malignant human tumor samples mostly coming from clinical trials and preclinical model systems, and on the continued development of genomic-based
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the consistency of predicted deformations with earthquake focal mechanisms. The first part of the project involves using numerical mechanical models to calculate crustal stresses arising from four main
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state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational campaigns. Key responsibilities Design and execute in silico protein and