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realistic oxide nanoparticles with sizes from a few 10s of atoms to several 1000s of atoms. In each case, machine learned interatomic potentials (MLIPs) will be developed to describe their structure and
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discrete choice modelling, behavioural data science or machine learning? Are you interested in developing the next generation of AI tools that accelerate scientific discovery while maintaining behavioural
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://www.ntu.edu.sg/eee. We are looking for a Research Engineer to develop machine learning models for recommendation systems. The role will focus on R&D activities including the development of recommendation system
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, including physics-informed neural networks, neural operators, hybrid physics-ML approaches, and emerging foundation-model paradigms for scientific data. Scientific machine learning is increasingly important
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. The increasing availability of electronic health records, clinical measurements, medical imaging and longitudinal health data provides opportunities for Artificial Intelligence (AI) and Machine Learning (ML
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, lifestyle and, where available, longitudinal patient data. Machine-learning and deep-learning methods will be developed and evaluated for early prediction, risk stratification and prognostic modelling
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with nuclear fuel modelling, machine learning
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activities. Your role As a professor in the Department of Computer Science, you will: Lead research in your area of expertise, with a focus on machine learning and foundation models, and have the opportunity
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of Computer Science, you will: Lead research in your area of expertise, with a focus on machine learning and foundation models, and have the opportunity to establish and grow your own research group within a
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initio reference databases for training of machine-learned models. Documented experience in developing, training, evaluating and validating machine-learned interatomic force fields for atomistic