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Field
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Associate Support development and documentation of Python-based Design Tool workflow for D-Suite Project Formulate and solve optimization problems, developing algorithms which have appropriate accuracy
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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systems, or equivalent, with a strong training in numerical optimization and optimal control. Additional training in machine learning and reinforcement learning is a plus. Your course of study must
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than conventional structures. Superstructure optimization, which uses a predefined architecture with numerous unit operations and possible paths, offers an alternative for identifying non-intuitive
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mechanical motion into electricity; - An intelligent electronic control system, enabling optimized regulation of the thermodynamic cycle. Within the CALIFORCE3 framework, the REMLA system will be integrated
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, multiphysics simulations, device implementation, and experimental validation. Key responsibilities: Develop theoretical and numerical models of piezoelectric energy harvesters under heavy-load conditions. Design
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material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property linkages based on numerical simulations and to transform them into AI
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-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up
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collaboration – for instance, in numerous Collaborative Research Centres (also known as CRC or sometimes CRC/TRR) and in application-oriented research assignments. The University of Stuttgart sets up a close
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dynamics and composites? Are you familiar with numerical simulation and optimization? You got some experience with data evaluation and analytics? Maybe you even have some knowledge of the wind industry and