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skills in coding for statistical and spatial analyses by relevant tools (e.g. R, QGIS and Python), as well as ability to manage large datasets of wall-to-wall environmental data. • Excellent oral and
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(most notably, distribution modelling); • Documented experience and skills in coding for statistical and spatial analyses by relevant tools (e.g. R, QGIS and Python), as well as ability to manage large
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criteria (experience and qualifications): Practical archaeological skills (survey, cataloging, creating typologies) Familiarity with augmented reality mapping (ARS), geographic information systems (GIS) and
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a strong quantitative background and extensive experience in scientific programing (using e.g., Python, Matlab, and/or Julia), as well as a strong interest in climate science and biogeochemical
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recordings FELASA certificate (or equivalent personal license to conduct animal experiments) is required. Fluent oral and written English communication skills Python, Matlab, R or other relevant programming
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analysis. Proficiency with statistical software (e.g., R, Stata, or Python) and transparent, reproducible workflows. Strong collaborative skills. Excellent written and spoken English. Desirable Experience
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public defence are eligible for appointment. The candidate must have a strong quantitative background and extensive experience in scientific programing (using e.g., Python, Matlab, and/or Julia), as
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related field. Documented expertise in machine learning and time-series modelling (e.g. LSTM, XGBoost, CNN). Strong programming skills in languages such as Python and R. Experience with phenotyping data
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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate