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methods, strong publication potential, good command of English, programming skills in MATLAB, Python, R, Julia, or similar. Experience in one or more of the following is an advantage: time series analysis
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of structured and unstructured data, web programming and high-level programming languages, Python or R programming language in particular. LanguagesPOLISHLevelMother Tongue LanguagesENGLISHLevelExcellent Internal
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mechanics) with data-driven techniques. • Proficiency in Python (NumPy, TensorFlow/PyTorch) and MATLAB. • Familiarity with deep learning architectures, particularly recurrent neural networks (e.g., LSTM) and
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modern machine learning models Strong programming skills in Python and experience building and maintaining research code Demonstrated ability to use modern AI-assisted and agentic coding tools effectively
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, and/or substantial open-source research contributions Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models Strong programming skills in Python and
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contributions Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models Strong programming skills in Python and experience building and maintaining research code
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willingness to become familiar with the other, as well as multi-agent systems and ontologies. 4. Excellent Python programming skills, and familiarity with standard machine learning libraries. 5
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backend and frontend applications for AI and data-driven platforms Develop and maintain web applications using Python, Flask, React.js, and related frameworks Implement clean, modular, and maintainable code
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with Bayesian inference or machine learning is an advantage. • Proficiency in Python and/or R; experience with probabilistic programming (Stan, PyMC, NumPyro) or deep learning frameworks (PyTorch, JAX
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of experience in logistics and supply chain management is an advantage. Those without relevant work experience but who have the technical skills are welcome to apply. Proficiency in Python or similar programming