153 machine-learning "https:" "https:" "https:" "https:" "https:" positions at Nature Careers
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Development of innovative experimental model systems for mechanistic investigation and translational validation of microbiome-mediated processes Advanced AI and machine learning frameworks for integrative multi
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of California, Santa Cruz, invites applications for a UC Cooperative Extension (UCCE) Specialist at the Assistant rank. For full description, please follow https://recruit.ucanr.edu/JPF00368 This position will
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processing, neuromorphic engineering, or a closely related field. A solid background in machine learning is expected, with interest or experience in spiking neural networks, temporal modeling, or bio-inspired
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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Caribbean populations of African descent. Most mechanistic insights derive from non-representative cohorts, limiting biomarker discovery and therapeutic precision. Recent multi-omic and machine learning
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interactions with local centres of excellence in artificial intelligence, machine learning, applied mathematics, and computational sciences Application Procedure We accept applications from students of any
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems
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, machine learning model applications, and real-time applications Opportunities to learn more about systems neuroscience and neuroengineering One on one mentorship with graduate students and postdocs
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with