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designing and building visualization dashboards. Research experience in human-centered AI, or in the integration of AI and machine learning methods into interactive visualization and analysis systems. Strong
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric
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, privacy-preserving technologies, adversarial machine learning, explainable AI, or secure software engineering. Collaborate and Translate: Work within a supportive team, present findings at national and
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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experience in computational optics, computational microscopy, machine learning. • Open to Fixed Term Contract. Req ID: 33874 Apply now
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applications for a PhD Research Fellow position in fairness in artificial intelligence, available at the Department of Informatics, in the Scientific Computing and Machine Learning (SCML) research group
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representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European
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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi