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against dynamic loads and fire impacts Research and development of AI-optimized, energy-efficient and sustainable small-batch gasification technology Development and Investigation of Wide-Bandgap
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learning, optimization, training pipelines, evaluation metrics, and validation strategies. Experience with multimodal AI (CV, NLP, tabular, sensor or IoT data). Familiarity with MLOps, versioning tools
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. Hands-on experience with Retrieval-Augmented Generation (RAG), vector databases (FAISS, Milvus, Pinecone) and embeddings. Excellent understanding of deep learning, optimization, training pipelines
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the ability to optimize chemical structures and predict their energy levels and spatial charge distribution; Extensive experience in the synthesis of novel organic semiconductor structures for use in OLED
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and experimental research in the field of plasmonic nanostructures and related nanosystems, including proficiency in analytical and numerical simulations, as well as machine learning methods; work
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optimizing data-driven solutions, machine learning models, and artificial intelligence systems applied in business and technological environments. Additional Information Benefits Meaningful work at KTU – one
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semiconductors and emitters and their application in optoelectronic devices as well as optimization of the characteristics of the devices. The research seeks to utilize emission mechanisms discovered in recent