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Europe | 11 days ago
-light scattering on coupling in MCFHost institution: CNRS-PhLAM, FranceSupervisors: Prof. L. Bigot (CNRS-PhLAM), Prof. Y. Quiquempois (CNRS-PhLAM)DC 4 – OpenProject Title: Innovative MCF amplifier
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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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external enrolment procedures. Selection criteria Demonstrated experience in programming and system development. Expertise in Python programming and data analysis. Experience developing Machine Learning
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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analysis and data processing. Strong programming skills in R (preferable) and/or Python, and experience or interest in weather prediction or climate models. Knowledge of machine learning, AI techniques, and
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. Additional binational support is made possible by the CNRS in France and the DAAD and the Alexander von Humboldt Foundation in Germany. Course organisation The research training consists of research work and a
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government background checks (allow for between 4 to 8 weeks) and complete any other CSIRO requirements. Selection criteria To be eligible applicants must: Have a basic understanding of machine learning