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techniques. Proficiency in R, Python, or MATLAB for data processing, geospatial analysis, and statistical modeling. Experience with time series analysis, spatial mapping, and oceanographic data interpretation
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largely unknown. In this sense, the aim of this proposal is providing a pervasive biome-scale analysis of soil C stock changes in pastures and integrated systems in Brazilian Cerrado. Several areas with
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reactors), biostatistical analysis and molecular biology is highly required. Key responsibilities The candidate will be expected to: Plan and conduct research as part of the research team and contribute in
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guide their research work. Candidate Profile Due to the multidisciplinary character of ACER CoE, the ideal candidate must have as well a multidisciplinary scientific profile: PhD degree in Electrical
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at improving production efficiency and addressing the challenges posed by the use of lower-quality raw materials. This role involves working with a variety of characterization and analysis techniques to evaluate
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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
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high-quality scientific publications Supervision of master and PhD students, providing guidance on experimental techniques, data analysis, and research methodologies. Job requirements: You have a PhD
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multidimensional network data. This involves developing efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks
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in relation to this job profile. A detailed curriculum vitae. Brief research statement. Contact information of 3 referees (PhD mentor, postdoctoral mentor if relevant, and a third referee familiar with