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: • Conducting substantive, methodologically rigorous quantitative research analyses • Participating in study design, quality assurance testing, documenting coding methods, and interpreting results; • Act as
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the master's degree has been awarded. The candidate must have good knowledge in atmospheric dynamics. Proficiency in scientific coding and data analysis (e.g., Python, MATLAB, R, C++, FORTRAN) is required
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projects. Have an outstanding research record commensurate with their level of experience as demonstrated, for example, through an outstanding thesis, publications, conference presentations, code etc. Have a
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presentations, code etc. Have a proposal which is within the AI in Science research remit and skills which fit the cohort of AI in Science fellows. Fellows will join the Eric and Wendy Schmidt Network
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outstanding research record commensurate with their level of experience as demonstrated, for example, through an outstanding thesis, publications, conference presentations, code etc. Have a proposal which is
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on research projects. Have an outstanding research record commensurate with their level of experience as demonstrated, for example, through an outstanding thesis, publications, conference presentations, code
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, control theory, or a related field. Strong statistical understanding and a talent for data analysis and visualization using Matlab or Python are expected. Specific experience with experimental design
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welfare benefits in the State Pension Plan . Opportunity for physical activities within working hours Salary PhD Research Fellow (code 1017): NOK 550 800,- a year. Further promotion will be based on time
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about data assimilation and calibration of models based on observational data. Experience in using Github or other platforms for version control and collaboration on code development Fluent oral and
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research outputs Data science skills, especially data analysis and prediction modelling Proven ability to write code in Python Experience working in a research team Excellent writing and communication skills