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academic and professional qualifications Proven research experience in the field of modelling and analysis of biological networks Solid foundation in mathematics and algorithmic design Strong programming
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. Communication efficient learning of deep networks from decentralized data. In Artificial Intelligence and Statistics, PMLR, 2017. [4] Rieke, N., Hancox, J., Li, W. et al. The future of digital health with
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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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the ability of neural networks to learn unknown posterior distributions distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this PhD thesis is to develop
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multilayer networks. Nature Communications 10(1):3969 Barral J, Jülicher F, and Martin P (2018). Friction from transduction channels’ gating affects spontaneous hair-bundle oscillations. Biophysical Journal
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and very good knowledge in quantitative and qualitative research methods Good knowledge of statistical software (e.g. SPSS or STATA or R or JASP) Strong commitment and the ability to work in a team
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mass spectrometry and cheminformatics software and workflows, primarily for target and non-target metabolomics, exposomics and environmental analysis within the Environmental Cheminformatics Group and
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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