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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 22 days ago
include: * Designing and carrying out studies; * Analyzing and interpreting data; * Publishing papers describing these results, all with the mentor. Career development of the Postdoctoral Trainee will be
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, Experience and Qualifications PhD in biochemistry, Biomedical Sciences or Chemistry. Mass spectrometry-based proteomics. Data analysis of large proteomics datasets. Experience in cell culture and molecular
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experience in Oxford Nanopore Technologies (ONT) sequencing and bioinformatics A track record of research in microbiome science, metagenomics, whole genome sequencing, big data analysis, machine learning, and
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available within the Department of Medicine, Division of Endocrinology in the Laboratory of Brain Behavior and Big Data at the University of Southern California. The applicant with work with PI and
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drive change and effectively communicate change. Detailed oriented and capable of managing large amounts of data, maintain detailed comprehensive records, analyze and organize information, have effective
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for agriculture, offering a key solution for Europe's climate and energy transitions. Conventional ammonia synthesis via the Haber-Bosch process is operated at large scale (over 160 million tons
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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-precision vertexing and tracking of charged particles. Past and current projects include the upgrades of the Inner Tracking System (ITS) for the ALICE experiment at the Large Hadron Collider (LHC) at CERN
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
Understanding the individual and relative motion of particles is fundamental to understanding transport processes in complex flows. Large-scale transport in atmospheric flows is well understood and measured by
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responsible for the teaching and research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data