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. To do so, you will combine atomistic simulations (density functional theory and ab-initio molecular dynamics simulations) with new machine learning models to parameterize machine learning force fields
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disassembly, reuse, and remanufacturing already at the early design stage. In this role, you will develop power converter integration concepts that support design for disassembly. Multi-physics simulation tools
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communications, fundamental knowledge on computing architectures, and advanced programming skills (e.g., Python, C++, Matlab/Octave). Experience with simulation, emulation, and modelling tools for signal
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good process simulation and sustainability assessment skills. The FrameBio PhD project, is part of prestigious Marie Skłodowska-Curie Actions (MSCA) Doctoral Network, a collaboration between 16 partners
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will: Develop robust control strategies that leverage semantic data structures for rapid deployment. Create workflows to bridge BIM, energy simulation engines (e.g., EnergyPlus, Modelica), and control
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will involve both computational predictions and experimental validation. The project will combine density functional theory calculations with machine learning and molecular dynamics simulations
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hybrid organic-inorganic glasses and compare their vibrational properties against each other as well as more established glass families. The project will complement molecular dynamics simulations with
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complex interaction patterns that may carry important biological information. By integrating deep learning, genome-wide simulations, functional genomics, and large-scale biobank data, AI:GENOMIX aims
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communications, signal processing, or related fields at master’s level is essential. This includes a thorough understanding of the fundamentals, as well as modelling, simulation, and evaluation tools such as
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letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale A copy of the abstract of your MSc thesis, and a copy of any publications you may