108 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" uni jobs at Zintellect
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pursuing. Discipline(s): Chemistry and Materials Sciences (12 ) Communications and Graphics Design (2 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (29
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breeding. Learning Objectives: As an ORISE intern at our Center, the candidate will primarily learn the principles of classical plant breeding with a strong lean on applied genetics/genomics. By
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signaling. Learning Objectives: The participant will gain skills in bioinformatics, genetics, data analysis, statistics, and artificial intelligence-based methods for protein modelling. The participant will
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breeding. Learning Objectives: The participant will gain skills in laboratory methodologies, experimental design, horticulture, genetics, data analysis, statistics, and plant pathology. The participant will
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and the production and purification of monoclonal antibodies. Learning Objectives: The participant will learn about reagent development and testing for diagnostic and vaccine product development in a
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Sciences (12 ) Communications and Graphics Design (2 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (29 ) Environmental and Marine Sciences (14 ) Life
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at the COSPRU. Learning Objectives: The participant will gain hands-on experience with in vitro cell lines and in vivo mouse studies. The participant will also gain hands-on experience in microbiota data analysis
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multidisciplinary team to execute studies and analyze data. Learning Objectives: The participant will gain skills in the conduct of this research by collaborating side by side with Federal scientists and technicians
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surveillance missions worldwide. Participating in the preparation of manuscripts for publication Developing leadership skills and roles in research projects Learning how a high-throughput laboratory at
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. Given data from such “in the wild” techniques, CCDC ARL researchers are seeking to apply machine learning methods to both predict behavior and make inferences about the underlying processes that generate