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proficiency for the purpose of conducting classes (and/or consultations) in this language fluency in Polish language strong computer literacy and readiness to learn new software tools readiness to teach classes
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Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic
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for the university and funding agencies. Job Requirements: PhD qualification degree in Computer, Electrical or Electronic Engineering or related field At least 3 years of relevant research experience in AI security
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of machine learning potentials for the simulation of nucleic acids, developed by the group of Prof. Rafał Szabla. The funding eligibility criteria limit the maximum experience after obtaining the first PhD
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states and the transcription factor combinations that drive them as well as predict new combinations with machine learning approaches. This project will encompass: analyse single-cell and multi-omics
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UiO/Anders Lien 24th March 2026 Languages English English English Join the inclusive University of Oslo as a PhD Research Fellow in Machine Learning, tackling real-world data challenges! PhD
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Experience in groundwater modeling. Strong skills and experience with GIS platforms (e.g., ArcGIS, QGIS) and spatial data processing. Skill and experience with machine learning. Have a publication track record
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Economics » Transport economics Economics » Valuation Economics » Veterinary economics Educational sciences » Education Educational sciences » Learning studies Educational sciences » Research methodology
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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of the successful candidate. (1) Develop multisource, frugal downscaling approaches. Most downscaling approaches presented in the scientific literature are Machine Learning (ML)-based. The proposing team's experience