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Field
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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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incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non
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. Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms). Integrating these predictions
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The Department of Medical Biosciences is offering a postdoctoral scholarship within the project “Developing computational tools for large-scale human intracellular signaling models”. The scholarship
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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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are crucial for weather and climate predictions, rain formation, and the water cycle. According to the Inter-governmental Panel on Climate Change (IPCC), cloud modelling is one of the least understood domains
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engineering for mobility platforms • AI/ML for transportation prediction, system optimization, and environmental/health impact modeling • Deployment of decision-support tools for public-sector clients
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The main objective of the project is to develop an instrument model to predict
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outcomes, and multi-OMICS profiles, the project will generate predictive models to guide safer and more effective, individualized steroid use. As such, the candidate will be responsible for data
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numerical simulations, quantitative model/data comparisons, and exploration of predictive scenarios. Dissemination: Participate in the scientific promotion of results (publications, conferences). The position