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Field
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includes both theoretical and experimental components. This fundamental research aims to open new perspectives on various topics: optimizing the stability of micro-mechanical systems, controlling the energy
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materials processing and characterization, optimization of process yield and increasing process volume, and investigating the detailed mechanisms behind each process step. Percentage Of Time- 20% 2
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, energy) or discrete manufacturing (e.g., electronics assembly, automotive, home appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault
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initiatives include developing advanced aqueous emulsion and suspension systems for spray coating, predictive modeling of packaging performance, and optimizing packaging designs for high-value product
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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language models and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research results in top-tier international conferences
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independently. PhD in a relevant field. Documented experience of 1D, 2D design and optimization or CFD work related to turbomachinery research will be considered a plus Assessment criteria This is a career
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to optimize phenotype/physiological space through mechanistic diagnosis and simulations; - Develop an AI-driven platform that fuses SB and real-time field spectral data to advance precision viticulture
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
images, including Positron Emission Tomography, temporal multi-modal MRI and Histology, which we use for models training and validation. Objectives A key research focus of our group is the optimization
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students. Qualifications: Required: PhD in Computer Science, AI, Data Science, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs