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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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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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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get
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purification and characterization of membrane proteins is strongly desirable. Previous experience of biophysical analysis techniques such as ITC, QCMD as well as cryo electron microscopy is highly valuable
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curious and motivated postdoc with a PhD in biomedical engineering, physics, materials science, organic chemistry—or similar—and a drive to explore new frontiers in science. 👉 Learn more and apply here
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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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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 a postdoc fellow
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activities aimed at developing and using biomarker analysis in blood samples for next generation cancer diagnostics. The work will also include studies in basic tumor biology, where we use various in vitro
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. Importance will also be placed on experience of qualitative methods for data collection and analysis. Given the character of the research project importance will also be placed on good knowledge of both
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microorganisms, and developing of spectral collection and analysis protocols that will allow this biochemical data to be effectively used to support optical microscopy-based deep-learning algorithms for species