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Field
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/Resume. Required Education and Experience PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field. Preferred Qualifications Strong publication record in top-tier AI
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Genome Curation Assistant (Jarvis ): an AI system that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting
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., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) may be involved. Training will be provided in all methodologies but prior experience with some
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communications, orthogonal time frequency space modulation, radar/sonar signal processing, and machine and deep learning. WORK PERFORMING: Individual will perform research generally in the area of statistical
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, multi-omics analyses and systematic bioinformatics techniques is a strong advantage. Excellent programming skills (Python/R) and a solid training in AI or machine learning are highly preferred. A strong
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the College of Liberal Arts at Purdue and will be involved in interdisciplinary projects including faculty from communication, psychology, and engineering at Purdue and Rice University. This is an academic year
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characterization, and machine learning. The role offers the opportunity to leverage Argonne’s world-class scientific capabilities and engage with a strong network of internal and industry collaborators. Position
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration. CfAI is a large research group in the Department of Physics at Durham University
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 3 hours ago
, the program administrator, or any other office or agency. Qualifications The ideal candidate would have some, but not necessarily all, of the following skills: A PhD preferably in Petroleum Engineering or a
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developing cutting edge analytic tools for studying the genome transformation and genomic activities. 70% - The candidate will be mainly focusing on developing machine learning methods and/or AI algorithms