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groundwater/geochemical modelling software (e.g., MODFLOW, PHREEQC). Experience with laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications
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of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
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of hire. MD or PhD. Research expertise in Ophthalmology, Biomedical Engineering, Computer Science, Data Science, Machine Learning One year’s work experience, or equivalent in thesis research and other
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of the post. Candidates without a master’s degree have until 1st of July 2026 to complete the final exam. Strong programming and artificial intelligence/machine learning skills. The candidate’s research
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doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo . The University of Oslo has a transfer agreement with all employees
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kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban
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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools
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Department: SOM KC Radiation Oncology ----- Radiation Oncology Position Title: Post Doc Fellow - ONC Radiation Oncology Job Family Group: Professional Staff Job Description Summary: Postdoctoral
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severity of cyber threats. Both defenders and attackers are now using Machine Learning (ML) and Artificial Intelligence (AI), therefore research is needed to investigate and design more advanced
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. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with an emphasis on pattern identification, prediction, or spatial risk mapping