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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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of funding. FLSA Exempt position, not eligible for the overtime provisions of the FLSA. Minimum salary threshold must be met to maintain FLSA exemption. Visit The Office of Postdoctoral Affairs to learn more
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a machine learning model (foundational model) to propose protocols of sequential induction of transcription factors to generate desired cell subtypes. The project will be conducted in close
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candidates will have strong past experience in scientific machine learning. Experiences in large language models, molecular modeling and simulations, and/or polymer science are preferred but not required
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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Zanna, the successful candidate will focus on developing generative machine learning models for complex dynamical systems for probabilistic forecasts. The postdoc will be expected to lead independent
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associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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–functional modeling of root system architecture. Phenomics data integration and high-dimensional trait analysis. Predictive breeding and quantitative genetic modeling. Machine learning approaches to genotype