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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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8 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer hardware Computer science » Digital systems Engineering
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distribution modelling Experience with spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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series analysis, machine learning approaches). Ability to apply data analysis and simulation skills to generate insights into operational changes or targeted retrofits that will enhance building energy
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questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g., machine learning, stochastic dynamic programming
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language (e.g., Python, R, Rust, JavaScript) Experience with data analysis, statistical modeling, or machine learning techniques Familiarity with handling large datasets (e.g., using SQL) and data pipelines
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Research Project“ Transforming Cardiac Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data” as a PhD-Position in machine learning. You will work alongside leading experts
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approaches that combine artificial intelligence, machine learning, natural language processing, and social sciences. This collaborative and cross-sectoral approach aims to produce robust methods for evaluating
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interest in neuro-behavioral sciences and a passion for behavioral signals. Demonstrable experience in advanced data analysis and data collection. Familiarity with machine learning and proficiency in Python