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Field
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generation of experts skilled in the combination of Operation Research and trustworthy Machine Learning. CoRDS goes beyond the state-of-the-art DDO methods by proposing decision support frameworks that combine
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global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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the AIM-PACE project, which aims at developing a new generation of safe-and-sustainable-by-design, bio-based and circular plastics by combining AI, microbial technology, computer modelling, and polymer
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intelligence, or related areas Experience with large language models, machine learning systems, software testing, program analysis, requirements analysis, or software quality assurance Strong programming skills
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, modelling, or computer-aided design (CAD) skills Specific Requirements Compliance with the MSCA Doctoral Network mobility rule Must not have a doctoral degree at the date of their recruitment Willingness
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systems, intelligent sensing, advanced materials, and nanoscale device technologies. The successful candidate will develop machine learning approaches (including generative models and physics-informed
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, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the above-mentioned research areas collaboration in national and international research projects, possibly
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models for intelligent environments. The primary area of research involves developing AI models that can learn to represent real-world phenomena based on various types of observations, including video
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languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects Knowledge of machine learning and deep learning frameworks, including