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position within the research project “Statistical Methods for Online Detection of Anomalies” (SODA), newly funded by the Norwegian Research Council and affiliated with Integreat – the Norwegian Centre
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gathering and/or recording of results using appropriate research methods. Participate in and/or present at conferences and/or workshops relevant to the project as required. Assist with the supervision
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simulation models of existing test structure geometries to enable simulation and optimization for specific PIC platforms Investigate methods to optimize test structure designs for more robust determination of
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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of the following areas will be a merit. Advanced AI methods development in Python or any other relevant programming language Computer Vision and image analysis Handling of large dataset Qualifications Applicants
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, develop, and optimize new methods and techniques to address critical project or functional area needs. Participants will improve existing or develop new laboratory methods and processes, read and adapt
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Computer/Information Sciences Internal Number: A-168130-3 General Description Professor Gillian Hadfield is seeking a highly-qualified postdoctoral scholar to join her team at the Normativity Lab in
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familiar with some of the key scientific debates on democratic threats and democratic innovation. • The projects the employs ethnographic approaches, multiple and multisited case studies and mixed methods
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for simulations, we aim to explore solution strategies to calculate the amount of water given meteorological data and map data. Here, in addition to traditional discretization methods such as finite elements and