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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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focusing on defensive actions or neuromodulation in small neural networks have revealed significant deviations in typical behavioral patterns among larva populations. These deviations either necessitate a
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is part of the NumPEx project (http://www.numpex.fr) which is endowed with more than 40 million euros over 6 years, starting from 2023. This project aims to build a software stack for Exascale
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, 2020, Proceedings, Part XIV 16. Springer, 2020, pp. 194–210. [8] C. Reading, A. Harakeh, J. Chae, and S. L. Waslander, “Categorical depth distribution network for monocular 3d object detection,” in
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with existing single-cell methods and software would represent a strong advantage. Excellent communication skills and team spirit, and an ability to work in autonomy are essential. Fluent English both
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Organize training sessions Library packaging and deployment The successful candidate will master the following skills and knowledge: Proficiency in modern C++ (C++14 and above) Software engineering and
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of genetic networks Interplay between chromatin architecture and gene regulation Candidates will use a combination of skills in molecular and developmental biology, instrumentation and data analysis to answer
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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the main bioinformatics software and methods (R, Python, Bash). Knowledge on large-scale genotyping/sequencing data analyses. Good level in statistics. Good level of written and oral English. Ease in a