16 Mathematics "Universitat Oberta de Catalunya" PhD positions at NTNU Norwegian University of Science and Technology
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17 Apr 2024 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Mathematical Sciences Research Field Mathematics » Other Researcher
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of data from laboratory-scale to full-scale. Required selection criteria You must have a professionally relevant background in applied mathematics, cybernetics, or engineering. Strong knowledge in wind
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of data. Required selection criteria You must have a professionally relevant background in computer science, applied mathematics, or engineering. Your education must correspond to a five-year Norwegian
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, statistics, mathematics, or a related area or in a related field or corresponding foreign doctoral degree recognized as equivalent to a Norwegian doctoral degree. In exceptional cases we can also consider
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Mathematics » Applied mathematics Technology » Energy technology Economics » Industrial economics Economics » Financial science Researcher Profile First Stage Researcher (R1) Country Norway Application Deadline
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the assessment of the candidate. Competence in mathematical modeling and languages for simulation or optimization of climate, energy, or transport systems (e.g., Fortran, Python, GAMS, XPress, Matlab). Competence
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selection criteria You must have a relevant background in computer science and engineering, communication, mathematics, or statistics. Your education must correspond to a five-year Norwegian degree program
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engineering Mathematics » Applied mathematics Technology » Remote sensing Technology » Mining Researcher Profile First Stage Researcher (R1) Country Norway Application Deadline 4 Apr 2024 - 23:59 (Europe/Oslo
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and research assistant Preferred selection criteria We seek a candidate with skills in quantitative data analysis, demonstrated by good mathematical and programming abilities applicable to geophysical
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PhD candidate will focus on mathematical modelling of emissions from industrial sites, aiming to predict the evolution of the emissions faster than real-time. This will involve the use of reduced order