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external enrolment procedures. Selection criteria Demonstrated experience in programming and system development. Expertise in Python programming and data analysis. Experience developing Machine Learning
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strong interest in computer science (software development, machine learning techniques, etc.) is desirable. · Applicants must have a maximum of 3 years of research experience after the PhD. · Language
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climatic conditions, using machine learning approaches based on isotopic data. SSIAs for δ13C, δ15N and δ34S in dentin collagen and δ66Zn in enamel to reconstruct the evolution of seasonal habitats and the
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learning new techniques and finding answers to problems. You want to take advantage of the opportunity to do your PhD in two different countries and learn from different cultures and expertise. Where
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analysis and data processing. Strong programming skills in R (preferable) and/or Python, and experience or interest in weather prediction or climate models. Knowledge of machine learning, AI techniques, and
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government background checks (allow for between 4 to 8 weeks) and complete any other CSIRO requirements. Selection criteria To be eligible applicants must: Have a basic understanding of machine learning
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neuroimaging (fMRI, MEG, iEEG) and behavioral data. This PhD position is part of the Natural Auditory Scenes in Humans and Machines (NASCE) project, funded by the ERC Synergy Grant, and hosted at Maastricht