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an advantage: plasma surface functionalization; electrode/electrolyte interfaces; battery degradation modelling; microstructure-resolved modelling; tomography or image-based electrode modelling; machine learning
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learning or a related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: implementation of signal processing
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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, pathology and outcome data Multi-agent and predictive AI development: Develop machine-learning components for patient-trajectory modelling, recurrence and survival prediction, and integrate them
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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the Defense Innovation Network Assistant (DINA) initiative. The position conducts applied and translational research in machine learning, natural language processing (NLP), retrieval-augmented generation (RAG
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, including gas turbines and combustion engines. We combine advanced computational fluid dynamics, theory, machine learning, high-performance computing, and experimental methods to investigate and model complex
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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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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and
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epidemiology, and AI-accelerated drug and therapeutics discovery. DS/AI-driven Natural, Physical, and Earth Sciences, including physics-informed machine learning, climate and environmental modeling, physics and