251 parallel-computing-numerical-methods "Multiple" Postdoctoral positions in Germany
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) Exchange and close collaboration with partners from physics, computer science, and social psychology Your Profile: Completed master`s degree followed by a doctorate in physics, computer science, mathematics
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application. Our aim is to develop innovative methods for the cost-effective production of personalised gene therapies using non-viral gene transfer. The research project is geared towards a future spin-off and
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-average doctoral degree (PhD or equivalent) in management, organizational psychology, sociology, economics, business informatics, or a related field, • With a solid knowledge of empirical research methods
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measurements as well as highest spatial and density resolution. Additionally, the highly coherent beam enables the application of phase contrast methods with a spatial resolution below 50 nm. Join the Cluster
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) Application Deadline 1 Feb 2026 - 22:59 (UTC) Country Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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sounding systems Basic knowledge on middle atmosphere dynamics and spectroscopic methods Fundamental programming skills in, e.g., Python, Julia, C/C++. Expertise in automatic data processing and handling
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postdoctoral fellows to conduct interdisciplinary research on the interactions between fungal pathogens and microbial ecosystems within the Fellows4Fungi programme at the Leibniz-HKI (Jena, Germany
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manufacturing Use and further develop CRISPR (epi-)genome editing methods in CAR T cells Using cellular (e.g., FACS) and molecular (e.g., single cell analysis, next generation sequencing) methods to characterize
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methods for the design, verification, and test of circuits and systems for conventional as well as alternative and post-CMOS computing technologies. Besides that, we have successfully applied the methods
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, and unmodeled dynamics remains a key challenge. This position focuses on developing and validating methods that jointly address safety, performance, and reliability of learning-based control and