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Field
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work effectively and generate comprehensive reports. Solid knowledge and practical experience in applying analytical techniques and developing predictive models (e.g., statistical modelling, machine
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locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
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positivamentela experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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. Knowledge on multiphase (gas-particle two phase system), thermal energy storage, and/or renewable hydrogen technologies. Familiar with application of machine learning and deep learning algorithms to fluid and
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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participants Ideally, practical skills in one of (a) programming, (b) machine learning, and/or (c) design Responsibilities Developing and conducting novel research projects individually and on teams Developing a
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, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted