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support monitoring and analysis of deployment behaviour. Adapt, develop, and learn new simulation, modelling, and imaging tools, including integration with real-time visualization frameworks such as
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will focus on multimodal perception (vision–language models), probabilistic state estimation and 3D mapping/SLAM, and graph-based representations (scene/knowledge graphs). The work is funded by a
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model selection and pruning using observational constraints, extend best‑match runs over multiple stellar activity cycles, and prepare datasets for ML analysis. Contribute to coupling global and local
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data-analysis methods to follow condensation across different length and time scales. Work closely with researchers at Aalto University and the Finnish Meteorological Institute, including colleagues
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Fingrid. Research focus Monitoring and data analysis: Apply and develop methods to estimate torsional oscillation frequencies, damping and amplitudes from phasor measurement unit (PMU) data. Analyse
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Structural and biophysical characterisation of protein-coated DNA nanostructures Evaluation of RNA encapsulation and delivery performance Analysis of structural, kinetics, and functional datasets Dissemination
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numerical/computational modelling methods (e.g. discrete element method or finite element analysis) Strong programming skills Good written and verbal communication skills in English Considered an
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the finite element code Numerical analysis of additional losses in the operating conditions of simulated variable-speed electric machines Validate the developed simulation models by experimental
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or power measurement is strongly preferred) Data analysis and analytical modeling — identifying the features that drive system behaviour and building compositional or analytical models from measured
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Laboratory rock mechanics testing to ISRM suggested methods Reliability analysis, Monte Carlo, or importance sampling, and reliability-based design Materials engineering relevant to liners, cyclic loading