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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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skills. Is confident using digital learning tools such as Python, SAS, Stata or similar. Holds (or will soon complete) a doctorate in Finance or a closely related field. Enjoys contributing to the wider
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of European projects (GUINEVERE, FREYA, MYRTE) or bilateral CNRS-SCK collaborations (MYRACL, SALMON). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6534-AURGON-050/Default.aspx Requirements
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, MYRTE) or bilateral CNRS-SCK collaborations (MYRACL, SALMON). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6534-AURGON-049/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD
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Python and PyTorch Assist in dataset preparation, preprocessing, and augmentation Run training and evaluation pipelines Analyze experimental results and document findings Collaborate closely with graduate
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data analysis using software Experience in R and python is a plus but not mandatory Good presentation and writing skills Proactive, independent, and solution-oriented way of working Fluent English
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of the most recent econometric methods to study the evolution of wealth accumulation from incomplete tax data. The applicant needs to have advanced programming skills in Stata, R and Python
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. Practical experience applying machine learning or deep learning methods to biological data. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM
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, including branching strategies, pull requests, and documentation-as-code. Ensure all analytical scripts (SQL, R, Python) are versioned, audited, and recoverable. Implement CI/CD (Continuous Integration
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, or interaction for robotic systems Deep learning or applied machine learning for robotics Practical experience with robotic hardware, software development (e.g., Python, ROS, PyTorch, TensorFlow), and AI-based