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funded by an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is a unified application form for all positions in the Optimization and Machine
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capillary pressure, and data-driven, physics-driven machine-learning. Applications are sought for a two-year postdoc position, and will work closely with an industry partner. The position will include a
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Application documents: 1) Brief cover letter, explaining your motivation for applying, 2) Detailed curriculum vitae (including your email address), 3) Complete transcript of grades from all your university-level studies. We do not ask for more information/documents at this point (but you can...
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Postdoctoral Researchers to work on research problems at the interface between a selection of the following areas: - Bayesian inference for deep learning - Generative modeling - Computational statistics
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understanding of Bayesian principles for Statistics and Machine Learning High proficiency in programming with languages, such as: C/C , Python (including pytorch/jax) A proven record of the ability of producing
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learning, deep learning, and AI) for analysis and prediction of genotypic variation Methodology (machine learning, deep learning, and AI) for analysis and prediction based on medical or biological imaging
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King Abdullah University of Science and Technology (KAUST) | Saudi Arabia, | Saudi Arabia | 3 months ago
Bioinformatics (generative protein design) Methodology (machine learning, deep learning, and AI) for analysis and prediction of genotypic variation Methodology (machine learning, deep learning, and AI
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Bioinformatics (generative protein design) Methodology (machine learning, deep learning, and AI) for analysis and prediction of genotypic variation Methodology (machine learning, deep learning, and AI
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Bioinformatics (generative protein design) Methodology (machine learning, deep learning, and AI) for analysis and prediction of genotypic variation Methodology (machine learning, deep learning, and AI
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methods for bioengineering Topics of focus include (but are not limited to): Automation and robotics Genomics Biological imaging Bioinformatics (generative protein design) Methodology (machine learning