49 parallel-computing-numerical-methods Postdoctoral positions at Nature Careers in Germany
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), located in central Berlin, is seeking a highly motivated postdoctoral researcher with a strong computational background to develop new methods for analyzing multimodal data from genetic and pharmacological
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on both fundamental magnetic interactions and applications for efficient energy conversion. We use element-specific methods such as X-ray absorption spectroscopy at synchrotron radiation sources and
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are seeking an excellent and enthusiastic post-doctoral researcher with a strong interest in computational microbiome research. The specific focus of the project will be tailored to the candidate’s interests
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toxins, as well as their native stoichiometry, assembly and maturation. To this end, a combination of methods including membrane complex reconstitution and isolation, biochemical and biophysical
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environment in the fields of science, technology and administration as well as for the education of highly qualified young scientists. The computational imaging group at DESY is concerned with the development
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program during the postdoctoral training. We are looking for an enthusiastic scientist with a desire to work on a challenging and timely project using state of the art technology as part of a friendly and
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consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We are seeking an excellent and enthusiastic post-doctoral researcher with a strong interest in computational microbiome research
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program during the postdoctoral training. Requirements: We are looking for an enthusiastic scientist with a desire to work on a challenging and timely project using state of the art technology as part of a
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. The candidate will have the opportunity to obtain additional external funding and develop an independent research program during the postdoctoral training. We are looking for an enthusiastic scientist with a
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand