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Details The aim of this project is to combine nanomechanical methods with modelling (i) to develop quantitative, predictive models for the behaviour of molecules in sliding contacts, and (ii) to understand
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Are you a researcher driven to understand and predict the fundamental mechanisms limiting lithium-ion battery performance? We are recruiting a Research Associate in Lithium-Ion Battery Modelling
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. However, in many real-world and latency-critical applications, performance cannot be assessed solely through final recognition accuracy. Instead, the value of a prediction strongly depends on its timeliness
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. Specifically, your research will provide critical insight for NGGM performance assessment and predictions. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research
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field. This approach is related to data assimilation, allowing for better prediction, control, and optimisation of turbulent systems in engineering, energy, and environmental applications
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: Textual Prediction of Survival (LLM classification & Attention Modelling) This project develops a model to predict patient survival by analyzing heterogeneous clinical documents. Unlike traditional methods
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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that contribute to the control of viral infectious diseases. The lab’s research focuses on two main areas: (A) developing AI technologies to predict genotype–phenotype relationships of viral proteins, and (B
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(Jumpei Ito laboratory), Department of Biological Informatics, Research Institute for Microbial Diseases, Osaka University aims to develop bioinformatics technologies that contribute to the control of viral
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accepted all year round Details Dynamic optimization is integral to many aspects of science and engineering, commonly found in trajectory optimization, optimal control (e.g. model predictive control, MPC