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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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30th April 2026 Languages English Norsk Bokmål English English PhD Fellow in Machine Learning Apply for this job See advertisement About us The Nansen Center is a Norwegian environmental research
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collaborations. We seek applicants with strong analytical skills, background in computational fluid dynamics and/or machine learning, and a genuine interest in advancing reliable scientific machine learning
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; - academic curriculum with background on the computer science and machine learning background; - previous research and professional experience on the scientific domains of the work. Additional Information
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of data analytics, machine learning or artificial intelligence methods is desirable. Personal qualities Strong ability to follow through on tasks and projects Motivation for the academic and research field
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resilience of bridges under climate change-induced hazards such as flooding, scour, and debris impacts. The research aims to develop advanced numerical models and machine learning tools to predict loads
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combine intracranial electrophysiological recordings in humans with behavioral experiments and advanced analytical approaches, including machine learning and statistical modeling. It has two main objectives
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to: compositional multiphase reservoir simulation upscaling or screening methodologies optimization of well positions and control strategies economic assessments machine learning or proxy-model based methods field
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resulting precipitation and extreme weather. We study global and regional climate change and are at the core of international community climate modeling efforts that also involve AI and Machine Learning. We
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studying for a doctoral degree in the arts, science, law, commerce or agriculture. Availability Available to New Zealand Citizen or Permanent Resident Students Our website uses tracking technologies to learn