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Field
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Vacancies PhD Position: Advancing Kinematic Couplings for Precision Alignment Applications Key takeaways The challenge This PhD research focuses on the advanced design and analysis of kinematic
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for improved cancer understanding, diagnostics, and
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techniques, data analysis with desirable knowledge of material characterisation, rheology and imaging. Scientific interest, dedication to research and career goal to work in physical science research
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analyse large, multidimensional 4D STEM datasets. Develop or adapt software tools (e.g. Python, MATLAB) for image reconstruction, phase mapping, and quantitative analysis of ferroelectric domain wall
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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helping them in their experiments, acquisition, analysis and interpretation of data. Another requirement would be the ability to write reports, make presentations and contribute to writing the grant
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of their machines is maximised, or machine downtime is minimised. The aim is to develop a smart sensor prototype and demonstrator for condition monitoring of low-speed bearings. The following objectives are defined
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. Proficiency in geospatial, 3D, and image-processing software for data collection and analysis. Experience working with GIS, QField, total stations, geophysical equipment, and drones. Experience in stratigraphic
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. Collaborate with people with diabetes, diabetologists, software engineers, and clinical psychologists to develop and validate prototype tools. Contribute to qualitative and mixed-methods research to ensure user
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: Microscopy, histology, and image analysis to phenotype root anatomy. Plant and root physiological measurements to determine the function of root phenotypes. Genome-wide Association Studies (GWAS) and