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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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current regulations. The position is classified under the job code “Stipendiat” (PhD position, code 1017). In addition to the base salary, a Svalbard allowance of NOK 44,640 per annum is provided. A 2
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-on experience with 5G access/core testbeds and open-source solutions Good experience with Infrastructure as Code tools, DevSecOps and/or AIOps practices Relevant publication activities will be considered
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find more information for applicants . Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017. A compulsory contribution of 2 % to the Norwegian Public Service
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scientific positions. We have a number of measures to promote equality. Salary and conditions In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,-per annum depending
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the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted
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. Experience with programming (for example Python/Matlab) and image analysis is highly recommended. Please share your GitHub code repository if you have one. In assessing the applications, special emphasis will
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qualifications, female candidates will be favored. Salary and conditions In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,- per annum depending on qualifications and
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promote equality. In case of equal qualifications, female candidates will be prioritized. Salary and conditions In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800
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NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality. Salary and conditions In the position of PhD Candidate, code 1017, your gross
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selection criteria Experience of scientific publishing. Knowledge and experience of machine learning, preferably distributed machine learning. Knowledge and experience of coding and information theory