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(CNTFET) for ternary computing. Semiconducting CNTs are ideal for transistor channels due to their material properties and 1-D structure. With the continuous need of improving transistor performance, CNTFET
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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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of the art in mathematical and numerical modelling of CO2 storage? This might be the right position for you! About the project/work tasks: About the project TIME4CO2 TIME4CO2 aims at advancing simulation
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the most relevant information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust
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) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization Econometrics Virtual power plants Power systems and/or
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with NORCE, NMBU, and other national and international partners. The PhD project will focus on integrating advanced photogrammetric techniques applied to historical aerial imagery with modern deep
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capillary flow, drop impact, and wetting in fibrous networks. The PhD research fellow will design droplet flow experiments on fibers and focus on droplet accumulation on fibrous structures when exposed to fog
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national and international partners. The PhD project will focus on integrating advanced photogrammetric techniques applied to historical aerial imagery with modern deep learning-based image classification
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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian
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sciences or medicine, with a proven track record of cardiac research Previous experience with molecular cardiology, viral transduction, cell transfections, animal models, immunoblotting, qPCR, cardiomyocyte