420 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions in United States
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development (e.g. quantum Monte Carlo, neural quantum states, tensor networks, machine learning and data science, dynamical mean field theory, diagrammatic Monte Carlo, etc.) Key Responsibilities Conduct
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should
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Posting Summary Logo Posting Number RTF00010PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post-Doctoral
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applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention to detail and follow-up skills Strong customer service skills and phone and e-mail etiquette USG Core Values
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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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terminal degree with deep knowledge of Artificial Intelligence and Machine Learning. Desired Qualifications Ability to help create scalable Artificial Intelligence workflows. Experience in working with
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Professor John Harlim and his collaborators, Yan Li in the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project