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utilizing real utility data and models to address practical problems. The ideal candidate will have an outstanding academic track record, well-developed analytical and problem-solving skills, and be a
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 13 days ago
, development, and training of machine learning and deep learning algorithms. Creation of accurate, robust, and energy-efficient models. Development of systems capable of predicting and making decisions in real
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by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research program aims at formulating and implementing advanced constitutive models
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that precede symptoms. You integrate MRI-derived features with biological and clinical markers to improve disease-progression models and early prediction. Would you like to know more about the different phases
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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neuroimaging data constrained by patient's structural connectivity and tractography • Using the results of the TVB model fits to stratify patients and predict disease progression • Organizing and unifying
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selectivity and permeability and ultrahigh water permeability combined with high salt rejection. The objective of this work is to construct atomistic models of MOFs/Polymers and Artificial Water-Channel
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experimental design. Deep expertise in predictive modeling, classical ML algorithms (e.g., decision trees, gradient boosting), large language models (LLMs), generative AI, MLOps, and AutoML using frameworks like
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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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—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from