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- University of Oslo
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Field
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MATLAB or Python) Desired qualifications: The ideal candidate should have: Demonstrated knowledge of fluid dynamics Experience with anisotropic viscous flow Experience with ice texture formation Skills in
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to work independently and collaboratively in multidisciplinary teams Desired qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput
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commonly used programming languages in the field (Python, MATLAB, IDL, Fortran, etc). Prior experience working in the field or other high stress environments. Outgoing and eager to work in a team setting
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. Desired qualifications: The following is a list of skills that are desired, but not required, for the position. Experience with Python and/or Fortran is advantageous. Advanced knowledge of quantitative
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programme may be given consideration. The suitable candidate must have: Strong programming skills (preferably Python or MATLAB) Experience with using satellite remote sensing data (ideally for polar
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Penetrating Radar Near Surface Geophysics Operation of planetary science instruments The Post Doc candidate must have experience in Python programming The Post Doc candidate must be eligible to be able to join
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qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C) Familiarity with
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with the North Sea or South Atlantic salt basins is an advantage. Experience of programming (Python, Matlab, Fortran) is an advantage. Applicants must be able to work independently and in a structured
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modelling. Applicants must have good skills in programming (e.g. Python, R, Java Script) Experience (for example a master project or internship) working with snow or the cryosphere is a requirement
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Programming languages such as Python, C++, Julia or similar as well as excellent English-writing and -speaking skills Furthermore, experience within: Knowledge of Hydropower planning and hydrology Graph neural