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trapping and analysis using state-of-the-art nanopore experiments. About the Project Our group has pioneered the development of the Nanopore Electro-Osmotic Trap (NEOtrap), a groundbreaking technique that
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10.01.2022, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d) for performing fundamental research in the frame of the project DrawOn funded by the Bavarian...
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interviews to assess health behaviours. Experience in a variety of qualitative analysis techniques such as thematic analysis and Interpretative Phenomenological Analysis (IPA), in addition to other mixed
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discourse and knowledge dissemination, we create a better and more sustainable society. We aim to have international engagement while also strengthening our visibility and focus on the local community
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components and nucleic acids interact and self-assemble. Apply data analysis and modeling to deepen understanding of nanoparticle architectures, and contribute to standardization-relevant method development
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moments. All these factors are highly dynamic in the way they interact to impact racing tactics and trends. The specific objectives include: Historical analysis of racing from the past 3-5 years across
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for household who stay indoors, and to prepare for emergency responses. Possible quantitative methodologies include concurrent time-series analysis of outdoor and indoor environment data, prediction model
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, you will: Design and perform fluorogenic and nano-photonic DyeCycling experiments. Write/adapt analysis code to process fluorescence trajectories and extract kinetic information. Evaluate bioconjugation
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systems design in Germany and Europe Active participation in scientific and public discourse (including publishing in peer-reviewed scientific journals) Your Profile: A completed Master`s degree in
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scientists. * Excellent oral and written communication skills. Preferred Qualifications * Familiarity with common NGS analysis tools. * Familiarity with tensorflow and/or pytorch.  * Demonstrated ability