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to design optimized growth media for animal cells lines used in biotechnology. This work involves the development and application of genome-scale metabolic models to characterize cellular growth and
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Collaborate with domain experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance
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quantification of pigments and binders. The work will include the generation of simulated spectral data based on physical models, the training and optimization of machine learning models, and their validation
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facilities, and validation. Job description Characterization of powdered materials for ink formulation DIW process development for ceramic and TE materials, including parameters optimization and evaluation
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the Job related to staff position within a Research Infrastructure? No Offer Description DATE OF PUBLICATION 31 MARCH 2026 The aim of the project is to develop and optimize an innovative method
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, machine learning, and optimization, broadly defined. Applicants working at the intersection of these areas, especially those applying theoretical and computational methods to problems in management science
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–activity relationships. Development and optimization of reaction conditions Optimization of photocatalytic protocols for selective reactions such as green hydrogen production or demethylation of biomass
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frameworks linking molecular interactions to cellular and network-level behavior (e.g. protein-protein interaction, PPI, network analysis) Optimize simulation codes and workflows for leadership-class HPC
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involve developing an approach that uses Knowledge Organization (KO) metadata and ontologies to optimize parallel processing and scheduling policies (via Kubernetes) for Machine Learning tasks. The fellow
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, aiming to expand research fields. It includes the theoretical systematization of database aesthetics and the development of case studies to propose solutions that optimize metadata use. Activities involve