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recycled, if they are contaminated with fungal biomass and mycotoxins. Therefore, control and prevention strategies for fungal contamination and growth is essential. The aim of this particular part of CEBE
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competence in control theory and system identification. You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. The following experience will
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across Europe. Your primary tasks will be to: Design and implement manipulation strategies for mobile robotic platforms operating in unstructured mining environments Develop control methods for physical
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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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, the identification of predictive features, and the construction and validation of statistical or machine-learning-based models. The postdoctoral researcher will be responsible for: Developing a
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(ORNL). Multiple positions are available to support R&D with different research focuses. They include innovations in joining and materials processing/synthesis, AI/ML for process monitoring and control
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on annotation, reconstruction, identification of the genome and characterization of cell states for each bacterial species. In addition, we will leverage a deep learning approach a powerful artificial
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stewardship: Version-controlled protocols, metadata standards for dielectric testing, and contribution to shared repositories (aligns with "high-quality datasets" and organizational effectiveness). Mentoring
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-miss reporting culture. Reproducibility & data stewardship: Version-controlled protocols, metadata standards for dielectric testing, and contribution to shared repositories (aligns with “high-quality
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identifier a copy of an identification document a list of published scientific, professional and popular science papers a proof of a doctoral degree in an interdisciplinary field (for degrees obtained abroad