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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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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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Conocimientos de programación de nivel medio a avanzado (lenguaje preferido: Java). Conocimientos básicos sobre machine learning. Capacidad para redactar artículos científicos de alta calidad (por ejemplo, tesis
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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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of user support services, including network support, training, and computer desktop support. This role involves end-user support and training, focusing on endpoint technologies (desktops, laptops
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science, artificial intelligence, computer vision, mobile robotics, machine learning, data science and analytics, or be able to demonstrate an equivalent professional practice and engagement. Previous experience in
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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
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. status in Marketing from an AACSB or regionally accredited program. The candidate’s academic preparation should qualify them to teach in one or more of the following areas: Marketing Research, Principles
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tools (e.g., FSL, FreeSurfer, AFNI, ANTs, fMRIPrep, QSIPrep) into standardized processing streams. Support advanced modeling approaches including network analysis, multivariate methods, machine learning
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scientists, and machine learning experts will be an essential and enriching component of the position. Strong candidates will have a background in machine learning and natural language processing (NLP), with a