398 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" research jobs at Nature Careers
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acquire their fate and establish precise connectivity with target brain regions during development, and how these processes are altered by stress and pathology. To address these questions, the team combines
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: https://obgyn.uchicago.edu/research/griffith-laboratory Required Qualifications: Qualifications needed for this position include a PhD in clinical psychology or a related field, such as psychology
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome
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diseases, Genome Biology, 2024 S. Hudaiberdiev et al., Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits, PNAS, 2023 S. Li et
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
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related to the exchange of momentum, energy, and mass. Significant challenges persist in understanding processes and feedbacks. The Land-Atmosphere Feedback Initiative (LAFI, https://lafi-dfg.de ) is an
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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climate change, fostering sustainable agriculture, and preserving global biodiversity ( https://www.psb.ugent.be/ ). In this respect, an important research topic of the center is the interaction between
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities