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communication skills in English Proficiency in programming and data analysis in the statistical software environment R, Python, or other relevant programming languages, as evidenced in relevant courses
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proficiency, particularly in Python Experience with or strong interest in, Language models (SLMs/LLMs), Agentic AI systems, Deep learning architectures, Multimodal AI (e.g., text, time-series, sensor data
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Matlab or Python) are required. Experience in time series analysis is an advantage. Knowledge of physical oceanography at high latitudes is an advantage. Applicants must be able to work independently and
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of results_0.pdf to calculate your points for admission. Applicants are expected to have: Good programming skills, preferably in Python Ability to develop and implement computational methods Ability to work
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analysis workflows (Python and/or Julia-based; HPC-oriented handling of large datasets). Depending on competence: contributing to research software development supporting simulations and/or data workflows
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. Appointment is dependent on the public defense of the doctoral thesis being approved. Experience with analysis of time-series of neural data Proficiency in programming custom analysis pipelines (e.g. Python
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). Proven experience in scientific programming and numerical computing (MATLAB, Python, or C/C++), including implementation of reconstruction algorithms and image processing pipelines. Experience with
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communication skills in English Proficiency in programming and data analysis in the statistical software environment R, Python, or other relevant programming languages, as evidenced in relevant courses
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degree has been awarded. A good understanding of ocean and/or climate dynamics is a requirement. Proficiency in scientific programming (e.g., MATLAB or Python) is a requirement. Experience in statistical
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to NeuroPathways Familiarity with quasi-experimental methods for causal inference Familiarity with administrative register data or other types of big data Familiarity with R, Stata, Python, or other relevant