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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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, material synthesis, catalysis, analysis and characterisation, battery cell, recycling, sustainability and life cycle analysis. Theory and Modelling Theoretical work is conducted on very different length- and
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susceptible steel structures. Thus, the candidate will develop reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be
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of Physics by means of various spectroscopy schemes and also at Q.ANT in their gyroscope/magnetometer labs. With this thesis, the PhD student will acquire broad knowledge on state-of-the-art laser technology
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to learn/develop new techniques. The ability to work both independently and in a team is essential. The postholder will hold (or will shortly complete) a diploma/master degree in molecular, cell or
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-Lettres network) or teach courses themselves (e.g. if obtaining a post/"contrat" doctoral at one of the institutions). Special promotion / funding of the programme Franco-German University (FGU) Course
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reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be complemented by own lab testing e.g., SSRT incl
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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reliable, conscientious, and structured work, commitment, initiative, teamwork skills, scientific curiosity, and willingness to learn willingness to be mobile (especially with regard to the required
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Kolter, Tjibbe Donker and Philipp Henneke analysis of multiscale single cell ‘omics data in in experimental and human models reference genome and transcriptome assembly and annotation across species