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. The division is an important part of the eSSENCE e-science collaboration and of the Science for Life Laboratory (SciLifeLab ) network, a national research infrastructure for life sciences. The successful
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of Materials Design and Innovation Posting Number R260134 Posting Link https://www.ubjobs.buffalo.edu/postings/64174 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term
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-mantle NCMASF3 system; ii) Training a Mixture Density Network emulator on 106 thermodynamic evaluations; iii) Implementing a global MCMC Bayesian inversion of the SPARTANS tomographic model; and iv
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via nonlinear parametrizations such as deep networks, dynamical systems and control, Bayesian inference and generative modeling, and randomized linear algebra. Applications of interest are transport
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that leverage state-of-the-art AI methods (deep learning, generative AI, Bayesian modelling, active learning, etc.) to combine cellular imaging data, chemical compound structure, viral genomes and other omics
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
. 5. Y. Ban, X. Alameda-Pineda, L. Girin, and R. Horaud, "Variational Bayesian inference for audio-visual tracking of multiple speakers," IEEE TPAMI, 2019. 6. X. Alameda-Pineda et al., "Socially
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other researchers (MSc and PhD students, post-docs and project researchers), as well as with an extended network of international collaborators. Job description The selected candidate will work on the ERC
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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Description The post-doctoral fellow will work on research projects related to the network applying a data management plan and statistical analysis plan design, epidemiology, causal inference, semi-parametric