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experiments, molecular cloning, cell culture, and standard laboratory methods such as flow cytometry and RT-qPCR. The computational work includes, for example, the analysis of omics data and computational
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analysis, work with large language models, network analysis, causal inference in machine learning and agent-based modelling. Experience in collecting, curating and analyzing large digital datasets with
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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We are seeking a highly motivated person to conduct research in economic modelling of forest resources to support analysis of environmental and climate change issues. About the position The project
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analysis, work with large language models, network analysis, causal inference in machine learning and agent-based modelling. Experience in collecting, curating and analyzing large digital datasets with
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criteria Assessment grounds that would place the candidate at an advantage include documented evidence of research in ecology, experience and knowledge in advanced complex statistical analysis (e.g
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Parkinson. We use in vitro biophysical analysis to characterise protein aggregates and their formation in combination with advanced live cell fluorescence imaging and cell model development to study protein
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will include clinical and biomedical research projects. It will also involve methodological development aimed at combining imaging techniques and data analysis to provide a more integrated understanding
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. It may also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be
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responsibilities As a postdoctoral researcher in the group, you will need to perform sample preparation, data collection and analysis work as agreed during regular meetings. You will also need to participate in