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and programming (MATLAB, Python, R, or other scientific coding/programming). Affinity with computational neuroscience, connectomics and/or Machine Learning is appreciated. Our goal perform connectome
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Social Participation). TACIT focuses on the co-design of inclusive and accessible AI and other technologies for people with disabilities through inclusive Human-Computer Interaction (HCI) and participatory
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. optimization and machine learning techniques) to prepare ports, terminals, shipping companies, and other port actors for this important challenge. Your research will be part of the PortCall.Zero project - a five
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eager to apply and valorize scientific results in this field in high-tech domains such as semiconductor machines and robots, together with highly innovative companies? Would you like to work in a team of
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the attractiveness to the users, we need innovative designs where fixed and flexible services support each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and
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will include boosted final states. The analysis strategy is strongly focused on advanced machine learning techniques, developing attention-based transformer models that will directly classify events from
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to protect AI models against data leakage during inter-departmental information sharing. With the National Police heavily relying on sensitive data exchanges, this research will develop secure machine learning
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considered an advantage. Technical Skills Proficiency in MATLAB, Python, and/or R. Experience with data science frameworks (e.g., AI, LLMs). Familiarity with machine learning (e.g., scikit-learn, MVPA, RSA
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opportunity to tackle these two complementary perspectives. In the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools
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: vibration measurement and analysis, AI/machine learning or signal processing Programming experience (e.g. Python, MATLAB, or similar) A creative and analytical mindset with an eagerness to pioneer new methods