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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and
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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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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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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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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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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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, C/C++ and/or Java, etc.; experience with the implementation of specialized transport modelling software, optimization algorithms and procedures; strong ability and desire to learn new programming
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systems using various tools and models, including: i) characterization of the emerging patterns in physical systems (solid state materials and active systems); ii) investigation of the mechanical properties
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PhD position in interpretable machine learning for dementia prediction. The project focuses on developing interpretable deep learning models for dementia prediction using multi-modal data, including MRI