149 evolution "https:" "https:" "UCL" "UCL" positions at DAAD

  • DAAD | Germany | about 2 months ago

    of inorganic ions and organic matter can cause defects in electrolyser stacks, resulting in costly process disruptions. This project considers: i) development of analytical methods for the quantification

  • DAAD | Germany | 20 days ago

    RTG3120 on Biomolecular Condensates ( https://dresdencondensates.org ). Each PhD project is part of an interdisciplinary framework that includes shared training activities, and supervision by

  • DAAD | Germany | 15 days ago

    numerical groups More information on the Junior Research Group can be found under  https://tu-dresden.de/mn/physik/itp/das-institut/ag/arbeitsgruppe-quantum-critical-matter?set_language=en . If you have

  • DAAD | Germany | about 2 months ago

    methods for photocatalytic membrane development.  The project will focus on i) photocatalyst selection, looking beyond the most commonly used materials, ii) exploring options of catalyst deposition and

  • DAAD | Germany | 2 months ago

    about the ISSE Institute, please visit our website:  https://www.isse.tu-clausthal.de Your responsibilities include: Research and development in the field of software engineering for dependable and safe

  • DAAD | Germany | about 1 month ago

    and contribute your own ideas flexible working hours and support in balancing work and family life comprehensive training and professional development opportunities a job ticket (public transportation

  • DAAD | Germany | about 1 month ago

    : Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic

  • DAAD | Germany | about 2 months ago

    research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine

  • DAAD | Germany | 3 months ago

    the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data

  • DAAD | Germany | 3 months ago

    position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context

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