43 parallel-and-distributed-computing research jobs at University of Bergen in Norway
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, dissemination or research infrastructure/services, will be distributed over the full employment period and thus corresponding to 25 per cent of the time each year. The employment period may be reduced if you have
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work associated with teaching, dissemination or research infrastructure/services, will be distributed over the full employment period and thus corresponding to 25 per cent of the time each year. The
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department upon appointment. If a 4th year is granted, one year of career-promoting work associated with teaching, dissemination or research infrastructure/services, will be distributed over the full
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at the department) distributed over the employment period. The 4th year is contingent on the qualifications of the candidate and the teaching needs of the department and will be decided by the head of department upon
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(e.g. teaching at the Institute). The position is associated with the research group in energy at the Geophysical Institute, the Bergen Offshore Wind Center and the energy informatics lab
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of 25 % career-promoting work (e.g. teaching responsibilities at the department) distributed over the employment period. The 4th year is contingent on the qualifications of the candidate and the
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. teaching responsibilities at the department) distributed over the employment period. The 4th year is contingent on the qualifications of the candidate and the teaching needs of the department and will be
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, with the possibility for a 4th year, consisting of 25% career-promoting work (e.g. teaching responsibilities at the department) distributed over the employment period. The 4th year is contingent
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to identifying and interpreting trends in regional-to-local scale signals and extreme events. Large ensembles of climate simulations are a key tool in such applications, but the computational cost of producing
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tool in such applications, but the computational cost of producing ensembles at high enough resolution and with enough members to adequately sample internal variability and capture rare events is a