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Field
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necessary to engage a qualified professional responsible for delivering e-learning training to primary and secondary school teachers in self-regulation and behavior modification strategies for children with
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been opened. The ideal candidate holds a master's-level background in robotics, AI or related fields, with strong Python/C++ skills and experience in machine learning or planning. Experience with ROS2
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Machine Design, Industrial Maintenance of Machinery and Automobiles, and Theory of Machines and Mechanisms. Additionally, the candidate will be expected to integrate into the department’s research lines
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explainable AI techniques, machine learning, Large Language Models, case-based reasoning, and ontologies. Specific Requirements Programming in python, XAI libraries, machine learning and deep learning libraries
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Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Personal Competences: Demonstrated competitive ability in using DFT simulations, and machine learning techniques and DFT. Demonstrated strong coding skills and a passion for UX/UI design. Summary
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hypotheses. The candidate will apply machine learning models to clinical and omics data for classification tasks. We are looking for highly motivated and organized candidates with good communication skills
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of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug
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to provide internal operational guidance and advanced tools that accelerate the adoption and development of machine learning (ML) methods across the centre. Its mission is supported by a set of strategic lines
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parameters affect material properties and functional performance, and interacting with machine-learning and modelling teams to translate experimental results into predictive datasets. Preparing reproducible
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integrating machine learning (ML) and molecular dynamics (MD) tools with experimental feedback, the project strives to accelerate the design of efficient and sustainable nanocatalysts, contributing