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Field
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academic or industry leadership roles. Your profile Applicants should hold a PhD in Computer Science, Electrical Engineering, Computer Engineering, Telecommunications, or a similar field, with a strong
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play a key role in the integration and analysis of omics data collected within the groundbreaking TREAT EARLIER trial. This trial is the first preventive study in the field of rheumatology globally and
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hands-on experience in tissue handling, histology, microscopy, and spatial transcriptomics. Experience with the computational analysis of NGS- or imaging-based spatial transcriptomics and single-cell
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preferred • Experience in image processing and analysis also preferred • The candidate will report directly to the Principal Investigator and will successfully carry out experiments and analyze the data
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) department at Telecom Paris. Reinforcement learning (RL) has emerged as a useful paradigm for training agents to perform complex tasks. Model-based RL (MBRL), in particular, promises greater sample efficiency
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well as an active engagement in the 3RTG activities. Requirements: successfully completed university degree (Master's, Diploma or equivalent) and relevant PhD in Computer Science, Computer Engineering, or related
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microscopy workflows to study battery materials and interfaces. Work with new approaches for preparing and transferring sensitive samples. Contribute to method development for imaging liquids and solid–liquid
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and/or image processing * Strong proficiency in programming with Python and Matlab * Good command of English Knowledge of solid mechanics would be an asset, but is not essential. Website for additional
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: Carrying out research in the predefined areas Implementing prototype tools Managing and contributing to national and international research projects Preparing project deliverables Disseminating results
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embedded in nanoscopic droplets of superfluid helium. Specific projects include, but are not limited to: 1) Time-resolved imaging of cation-molecule complex formation 2) Time-resolved stereodynamics