75 machine-learning-"https:"-"https:"-"https:"-"ISCTE-IUL" Fellowship positions at Zintellect
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, leading to peer-reviewed publications. The fellow may also have the opportunity to be included in helping with the USDA new world screwworm response. Learning Objectives: The fellow will learn techniques in
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operational scales. Learning Objectives: The participant will gain hands-on experience and acquire knowledge in engineering solutions for nutrient recovery and/or removal from manure and animal wastewater, as
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of biocontrol treatments in corn. Learning Objectives: Through this fellowship, the successful applicant will gain valuable hands-on experience and develop expertise in laboratory and field research
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of innovations that mitigate negative outcomes from these relationships. Learning Objectives: You will learn and apply skills in microbiology, virology, insect biology and beekeeping to explore host-virus
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of biocontrol treatments in corn. Learning Objectives: Through this fellowship, the successful applicant will gain valuable hands-on experience and develop expertise in laboratory and field research
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scientist Dr. John Newman. Additional techniques that may be incorporated in the project include multi-color flow cytometry, RNA-sequencing, and ELISA. Learning Objectives: In this opportunity
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Transkingdom Microbial Community Assembly in the Barley Phyllosphere During Fusarium Infection.” Learning Objectives: Under the guidance of a mentor, the participant will learn how to: Perform statistical
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this information can improve our ability to predict the spread and intensity of wildfires and prescribed fires. Learning Objectives: The program participant will learn a variety of new skills to measure
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to improve soybean for enhanced disease tolerance by accelerating breeding programs and enabling the engineering of new and improved traits. Learning Objectives: As a result of this experience, the participant
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will focus on evaluating how alfalfa-grass interactions influence biological nitrogen fixation, soil health, and soil organic matter dynamics in mixed species forage production systems. Learning