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environments Interest in industrial monitoring systems, smart sensors, and sustainable manufacturing Experience with sensor data processing or instrumentation systems Knowledge of machine learning or anomaly
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic
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research. Experience applying machine learning and statistical modeling techniques to large biological datasets for biomarker discovery, disease prediction, or host-pathogen investigations. Proficiency in
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 1 month ago
systems Computer science » Informatics Information science Information science » Information management Researcher Profile Recognised Researcher (R2) Application Deadline 31 Mar 2026 - 12:30 (UTC) Country
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agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and behavioral well-being, particularly among vulnerable populations. Applicants are encouraged to approach
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costs and energy requirements of state-of-the-art deep learning models significantly, while democratizing them for a vast community of users, researchers, and practitioners. The task is to perform just
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Networks. Knowledge of and experience in Python, TensorFlow, Keras, or other Machine Learning toolboxes, is essential. Knowledge of and experience in Large Language Models is highly relevant. The successful
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machine learning (ML) models and optimization algorithms specifically designed for highly dynamic satellite communication (SatCom) systems that can handle networks of varying sizes and configurations
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs