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for secure and resilient systems; privacy; secure sensing and control in critical infrastructures) Candidates with a PhD in Electrical Engineering, Computer Engineering, Computer Science, or other closely
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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and photonics Neuromorphic computing, artificial intelligence and machine learning Quantum and 2D materials technologies & systems Micro and nanoelectromechanical systems (MEMS/NEMS) Electromagnetics
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Investigating cyber-physical power system resilience and operation School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Xin Zhang Application Deadline: Applications
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, supply chain systems, and transportation systems. We also currently host methodological research in data analytics, machine learning, human systems engineering, optimization, simulation, and stochastic
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02215, United States of America [map ] Subject Areas: Data Science / Artificial Intelligence , Data Engineering , Machine Learning , Statistical Inference Computer Science / Artificial Intelligence
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quality monitoring, and/or nature-based water treatment designs. In addition, the candidate should have some experience in AI, machine learning, and/or managing large data sets related to water resources
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, G. et al. Machine learning and wearable sensors for automated Parkinson’s disease diagnosis aid: a systematic review. J Neurol 271, 6452–6470 (2024). https://doi.org/10.1007/s00415-024-12611-x Nayan
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UiO/Anders Lien 8th March 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat