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, knowledge-driven models and AI-based decision support can be integrated to support resilient and energy-aware manufacturing systems. Special emphasis will be placed on multi-objective optimization, learning
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optimization algorithms is highly desirable Excellent programming skills in Python, C++, Java, Julia, or other relevant languages Knowledge of maritime decarbonization and alternative fuels is a plus A good
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, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization, energy management, or production scheduling. Good knowledge of integrated energy
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Take the next step in your research career at the intersection of digital twins, multi-timescale system optimization, and integrated Power-to-X systems with special focus on the electrical
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processes. Ensure consistency and accuracy across imaging datasets and labeling workflows. Machine Learning & Model Development Support the design, development, and optimization of machine learning and deep
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characterization of tissue simulants and non-Newtonian materials, including support for 3D printing and additive manufacturing processes. Develop and optimize experimental setups, testing protocols and data
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• Possess a PhD in a related discipline (transportation engineering, operations research, computer engineering/science, or related disciplines) by December 2024. • Strong knowledge and
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of domain-specific data and knowledge. Develop new tabular foundation-model approaches where existing pre-trained models are insufficient, with a particular focus on transferability across heterogeneous
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral position in microfluidic RNAseq-based screening for optimal T-cell expansion
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research teams: 1) The AI Group: Experts in systems, control, optimization, Large Language Model (LLM) training, domain adaptation, and instruction tuning, agentic AI orchestration, and reinforcement