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of the division of Environmental Systems Analysis at Chalmers Institute of Technology, and Dr. Aaron Rice of the K. Lisa Yang Center for Conservation Bioacoustics at Cornell University. The positions include
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. Experience in scientific programming (e.g., Matlab and Python) is a requirement. Experience with analysis of climate data sets is an advantage. Applicants must be able to work independently and in a structured
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in Integreat and secondly, in a co-authored publication together with Anna Smajdor, based on ethical analysis of the findings from the overall project. In addition to the research activities described
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PhD Research Fellow in Experimental Fluid Mechanics: Tunable hairy surfaces for droplet flow control
, complex analysis and logic. We have almost 50 persons in permanent academic positions and a large number of post docs and Ph.D. students. We also have an administrative and technical staff. The department
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risk, algebra, geometry, topology, operator algebras, complex analysis and logic. We have almost 50 persons in permanent academic positions and a large number of post docs and Ph.D. students. We also
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, operator algebras, complex analysis and logic. We have almost 50 persons in permanent academic positions and a large number of post docs and Ph.D. students. We also have an administrative and technical staff
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sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C) Familiarity with SUMOylation, transcription factors, or chromatin dynamics Expertise in statistical modeling for biological data. Knowledge
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an approved doctoral thesis and public defense are eligible for appointment. Good knowledge of programming and data analysis using Fortran, Matlab, Python, or similar programming languages. Experience in using
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. Potential methodological topics focus on meta-analyses and the analysis of large-scale assessment data: Methods and approaches to synthesize large data sets via meta-analyses (e.g., meta-analyses of large
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-dimensional data, survival and event history analysis, model selection and criticism, graphical modelling, non-parametric methods, machine learning, hierarchical Bayesian modelling, and time- and space