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PhD position in Experimental Physics with focus on photonics and materials science (applied aspects)
information processing and investigate how structured ultrashort light pulses can control optical and magnetic properties on femtosecond timescales. The research will focus on developing sub-10 fs protocols
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for screening the subsurface to select areas with H2 -potential source rocks; - acquire and process new MT and controlled-source electromagnetic (CSEM) field data in targeted areas; - perform integrated 3D
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specialised stroke care and neurointerventional services. The PhD student will analyze and process large research datasets, interpret and evaluate scientific results, and contribute to the writing and
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ceramic coatings. The position involves conducting application-inspired basic research on thin film materials where the main goal is to develop new environmentally friendly surface coating processes with
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four-generation family trees with financial information derived from probate inventories. The main phase of data collection has now been completed, and the project is entering a stage of data processing
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qualitative process methods (path tracing) and semi-quantitative network methods (socio-technical configuration analysis, STCA), and contribute to the project's methods development compare cases across sectors
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environmentally friendly surface coating processes with maintained layer quality, functionality and reduced energy consumption. The project is carried out in close collaboration with Swedish industry. Publication
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7 Jul 2026 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Engineering » Control engineering Engineering » Electrical engineering Engineering » Systems
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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, Bayesian inference, model calibration, and Markov Chain Monte Carlo methods, uncertainty quantification, statistical modelling, and Gaussian processes, machine learning for time series, sequence-to-sequence