18 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Kaunas University of Technology in Lithuania
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applied machine learning. Location: SustAInLivWork Centre of Excellence (CoE) (Artificial Intelligence Centre of Excellence at Kaunas University of Technology (KTU)), Kaunas, Lithuania. The role requires a
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of professional experience in Python, C#, and Java, and extensive hands-on work with state-of-the-art machine learning frameworks (PyTorch, TensorFlow, JAX, Hugging Face Transformers). Demonstrated expertise in
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systems, copilots, AI assistants, no-code/low-code AI tools). Understanding of AI system deployment concepts and practical constraints relevant to business environments. Familiarity with machine learning
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methodologies, including machine learning, deep learning, TinyML, federated learning, explainable AI (XAI), digital twins, and other emerging techniques relevant to the RGs. Support interdisciplinary research
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, applying it to data analysis, econometric modelling, machine learning solutions, and the automation of research and data processing; Practical experience in the IT industry, developing, deploying, and
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, and comply with the applicable regulations and procedures of KTU. Where to apply Website https://karjera.ktu.edu/en-GB/jobs/6887543-project-expert-performing-as-head-of… Requirements Research
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the applicable rules and procedures of KTU. Where to apply Website https://karjera.ktu.edu/en-GB/jobs/6888146-project-expert-performing-as-head-of… Requirements Research FieldOtherEducation LevelMaster Degree
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the Center's internal rules, perform the duties defined in the official CoE documents, and comply with the applicable regulations and procedures of KTU. Where to apply Website https://karjera.ktu.edu/en-GB/jobs
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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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or multimodal physiological signal analysis; Experience applying machine-learning or advanced statistical methods to biomedical data, preferably in a physiology-informed, hypothesis-driven, or interpretable