488 machine-learning-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Nature Careers
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, convolutional and recurrent architectures, and transformer-based models, as applicable to biological, imaging, and multimodal data Hands-on experience with machine learning and deep learning frameworks (e.g
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, plant transformation, plant breeding, computer vision assisted automated phenotyping, machine learning and AI. The role will require working with other institutional stakeholders to scope, design, equip
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months in duration and can be customized to meet participants' individual learning goals. Participants have the opportunity to manage patients with a wide variety of infectious diseases on both
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Postdoctoral Position (f_m_x) in Environmental Seismology in an interdisciplinary ecohydrological...
(including time series analyses and machine learning) Good programming skills Very good communication and interpersonal skills, team player Very good command of English Experience in writing scientific
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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning
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the organization. Your profile Bachelor's or master's degree in computer science, computer engineering, cybersecurity or a related field and relevant security certifications (e.g., OSCP, CCSP, CISSP, CISM) from a
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molecule cellular accumulation and compiling a proteome-scale atlas of chemically tractable vulnerabilities. The project will accomplish this by 1) using high-throughput mass-spectrometry and machine
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of competitive research proposals. You should have experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction
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for early-stage cancer using statistics and/or machine learning (including deep learning where appropriate). You will join a vibrant and growing research group of 12 scientists (six postdoctoral researchers
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this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a