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- University of Bergen
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- NTNU Norwegian University of Science and Technology
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of the position. Demonstrated competencies and skills within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a requirement, and knowledge
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within programming and statistical analyses (e.g., in Python, R, etc) are a requirement. A background in media technology & AI is a requirement, and knowledge in the centre’s research areas. The applicant
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learning, e.g. using JAX, based on numerical models such as Higher Order Spectral method, mcsimpy, etc. Collect real metocean data from relevant online databases, datastreams such as from R/V Gunnerus, and
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. using JAX, based on numerical models such as Higher Order Spectral method, mcsimpy, etc. Collect real metocean data from relevant online databases, datastreams such as from R/V Gunnerus, and experimental
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, Atmospheric Science, Environmental Science, or related fields Good knowledge and skills in statistics and programming (e.g. R or Python) is required Experience with data analysis related to terrestrial ecology
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is supervised by Professor Amir R. Nejad and Professor Ole Andre Øiseth . Your immediate leader is Head of Department. Duties of the position Development of integrated condition monitoring system
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: Required qualifications: Experience with data analysis and familiarity with statistical software (e.g., R, Stata) The applicant must be fluent in oral and written English, see documentation requirements
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software (e.g., R, Stata) The applicant must be fluent in oral and written English, see documentation requirements Ability to work both independently and as part of a multidisciplinary and international team
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knowledge about natural resource management Knowledge of software R Strong skills and/or interest in mathematical and statistical modelling is a strength Ability to conduct field work in remote alpine areas
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. Experience with epidemiology and statistical analysis, including the use of statistical software such as STATA, R, or SAS, will be viewed positively. Documented or demonstrated ability to work independently