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applications. The project integrates: Computational Fluid Dynamics (CFD) and multiphase flow modeling Radiative heat transfer Machine learning and reduced-order modeling Data-driven optimization for industrial
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following areas: AI and machine learning, natural language processing, large language models (LLM), experience in designing prompts, fine-tuning LLMs, or distributed systems. Good knowledge in one or more of
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Scotland Innovation Hub to provide a secure cloud computing platform for Federated Learning and Machine Learning model development, and clinical researchers from NHS Greater Glasgow and Clyde. The successful
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California State University, Northridge | Northridge, California | United States | about 9 hours ago
data solutions. Expert knowledge of data modeling, statistical analysis, machine learning, and optimization techniques. Expert in leading and executing complex, high-impact data analytics projects and
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includes, but is not limited to: photonic data processing and communication systems; AI-driven optical signal processing and network optimisation; machine learning for photonic systems modelling, control
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learning spaces while modeling healthy lifestyle practices. What You’ll Do: Teach fitness classes using safe, effective, and appropriate methods tailored to participant skill levels. Plan and deliver
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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or similar) Preferred Qualifications: Experience with MRI/fMRI/DTI, PET, multimodal fusion, and/or machine learning Strong programming skills (Python/MATLAB), version control, and HPC workflows Special
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Rock is a metropolitan research university that provides an accessible, quality education through flexible learning and unparalleled internship opportunities. At UA Little Rock, we prepare our more than
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slowdown at the glass transition, remains a major computational challenge. This Doctoral student project addresses this by combining generative AI models and machine-learned interatomic potentials