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Field
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experiments and processing geological samples A theoretical background in thermodynamics, mineralogy, petrology and economic geology Statistics and coding experience A willingness to experiment with new data
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the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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fundamentals Strong programming skills in at least one relevant language (e.g., Python, R, Rust, JavaScript) Experience with data analysis, statistical modeling, or machine learning techniques Familiarity with
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, and a structured approach to problem-solving. Additional qualifications Coursework or other experiences with the following subjects are valued: scientific computing, optimization, statistical machine
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Environmental behaviour o Spatial analysis applied to territorial/regional planning Technical and soft skills · Basic computer skills (Word, Excel etc.) · Proficiency in statistical analysis
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mathematical concepts such as optimization, linear algebra, probability, and statistics, relevant to AI and quantitative modelling. Technical proficiency in programming66: Demonstrated programming skills with
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, Cascais, Riga, Vilnius, Melsungen, Ciampino, Urla and Rhodes. The PhD project will involve: The use of data analytics (statistical models, machine learning, uncertainty quantification) to monitor and
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research methods, including (but not limited to) longitudinal survey research, (automated) content analysis, and experiments; proven proficiency in statistical software such as SPSS, Stata and/or R; a
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, sequencing and analysing plant microbiomes, including bioinformatics and statistics as well as in working with oomycete plant pathogens are merits. Candidates should be fluent in written and spoken English. As