16 multi-scale-composite-wind PhD positions at Maastricht University (UM) in Netherlands
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interdependently on a common goal. The current project applies both laboratory and field study designs to investigate how such multi-team systems adapt to unexpected events. Thereby we specifically focus on the role
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patients. Investigating the best diagnostic strategies and treatment options. Exploring mechanisms of bleeding with innovative diagnostic tests, multi-omics, and fundamental research. Main endpoints include
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role of neural rhuthms for inter-area brain network communicartion PHD2: The neural code for multi-item representation in working memory PHD 3: The dynamic interplay between brain and bodily rhythms in
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experience in scientific publishing is preferred. Project management skills for complex, multi-stakeholder research. Willingness to work in both clinical and laboratory/field settings. Are you ready to make
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://www.coe.int/en/web/common-european-framework-reference-languages/table-1-cefr-3.3-common-reference-levels-global-scale What we offer As PhD candidateat Faculty of Arts and Social Sciences, you will be employed
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addition, we offer you: Good employment conditions. The position is graded in scale P according to UFO profile PhD Candidate, with corresponding salary based on experience ranging from €3.059 to €3.881 gross
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scale P according to UFO profile PhD, with corresponding salary based on experience ranging from €3059,00 and €3881,00 gross per month (based on a full-time employment of 38 hours per week). In
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change, healthcare shortages and the design of fair and efficient markets? Are you excited about advancing economic theory and measuring citizens’ preferences and attitudes on a large scale? At Maastricht
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that stimulate the regeneration of damaged or diseased tissues and organs. Research activities are structured into three flagship themes, each addressing increasing levels of length scale and structural complexity
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) for terabyte-scale 3D histology images, from preprocessing to analysis and validation. Handle and visualize large 3D microscopy datasets. Image optically cleared and labelled samples with 3D microscopy methods