31 phd-mathematical-modelling-ecological-modelling PhD positions at NTNU Norwegian University of Science and Technology
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Engineering » Materials engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 14 Mar 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job
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the reversibility of their phase transformations. In this project, the PhD Candidate will be responsible for conducting experimental studies into the basic mechanisms of alloy-anode materials using model electrode
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First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 13 Apr 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job
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Detection and Machine Learning (IEL) PhD in Power Grid Modelling for Net-Zero Energy Systems (IEL) PhD in Incorporating Distribution Grids in Multiscale Stochastic Energy System Models (IØT) PhD in Aspects
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First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 17 Mar 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job
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characterisation (e.g. space charge measurements, dielectric response in time and frequency domain, TGA, DSC, DMA, FTIR etc.). PhD #2 Numerical modelling of the ageing of HVDC cable insulation: Numerical models
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Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 31 Mar 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job funded
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First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 30 Mar 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5 Is the job
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» Materials technology Engineering » Process engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 23 Mar 2025 - 23:59 (Europe/Oslo) Type
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theory (state observers, parameter identification), mathematics of partial differential equations, modelling and simulation, machine learning/reinforcement learning. Experience with design of state- and