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Field
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is a requirement. Such experience may have been obtained through academic coursework, research projects, or professional employment. Experience with scientific programming using Python, R, Matlab
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quantitative skills are required. Experience and/or a strong interest in meteorology is an advantage. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency
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events and in machine learning for the earth system is required Strong and demonstrated programming skills are required Prior experience with geospatial data analysis in Python, working on scientific HPC
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. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency in geospatial data analysis is an advantage. Applicants must be able to work independently and in a
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/optimization/programming software (e.g., HOMER, GAMS, and Python). Evidence of previous scientific writing or academic publications (e.g., peer-reviewed journals), industrial collaboration, knowledge transfer
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the master's degree has been awarded Solid background in mathematics and physics is a requirement Experience in scientific programming (e.g., Matlab, Python) is requirement Experience in statistical analysis
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metrology, profilometry or microscopy, together with statistical analysis in R, Python or equivalent software. Dental crown materials, restorative dentistry, prosthodontics or dental laboratory workflows
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, e.g. in Python, particularly for machine learning Experience with machine learning theory, evaluation metrics, algorithmic fairness, statistics, or optimization is an advantage Language requirement
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and simulation using tools such as MATLAB/Simulink, DIgSILENT PowerFactory, OpenDSS or equivalent programming in Python, MATLAB or similar languages optimisation, control theory, machine learning
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modeling/simulation tools (e.g., MATLAB/Simulink, Modelica, and COMSOL Multiphysics), energy systems analysis/optimization/programming software (e.g., HOMER, GAMS, and Python). Evidence of previous