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Field
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. Required Qualifications Education: PhD or equivalent in demography, sociology, epidemiology, public health, or other health research-focused social science. Students currently enrolled in a doctoral program
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Identification of soil invertebrates (e.g. mites, springtails, insects) using modern and classical techniques Laboratory analyses of soil properties Statistical analysis of complex ecological datasets Presentation
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 5 days ago
develop state-of-the-art theoretical and computational methods to model strong light–matter coupling in and out of equilibrium, across gaseous, liquid, and solid-state systems. Key responsibilities The PhD
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experience: Essential criteria PhD in neuroscience, neuroimaging or related discipline. Experience and knowledge of performing functional MRI experiments Proficiency in the use of statistical packages (e.g. R
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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Geometry, Analysis and Probability Theory, and Applied Mathematics and Statistics, and conducts successful research in pure and applied mathematics and mathematical statistics in a wide range of research
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computer programs to design experimental paradigms, analyse data and conduct advanced statistical analysis. Prior experience in running neuromodulation studies including TMS and TUS is essential. You will be
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to develop robust experimental designs, to conduct data processing and statistical analysis with relevant programming language(s) (such as Python and R), and to handle high-dimensional research data to a high
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may be taken into consideration. A suitable candidate will have a PhD in computer science, statistics, sociology, economics, political science or a corresponding subject of relevance to computational
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(e.g. Presentation, PsychoPy, E-Prime, Gorilla). You have experience in data analysis, visualisations and programming in R and/or Python. You have experience with statistical models (e.g. mixed-effects