283 machine-learning "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions at Zintellect in United States
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generated quickly and regularly. Help develop machine learning techniques for feral swine abundance in data sparse environments. Collaborate with APHIS Wildlife Services (WS) to integrate data and model
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to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
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research applying artificial intelligence (AI) and machine learning (ML) techniques to analyze cervid movement patterns. GPS telemetry data obtained from free ranging cervids will be used by the participant
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uses cryo-electron microscopy to understand how viral proteins are recognized by antibodies at an atomic level, and how that recognition can be exploited to design effective vaccines. You will learn
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high school seniors, who are pursuing undergraduate studies in STEM, with an opportunity to explore the world of agricultural science through hands-on learning experiences. Participants will have the
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necessary to become credentialed as a Principal Investigator Applying a broad range of statistical and machine learning methods to human performance data collected in real-world settings Developing
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expanded to other microbiome related diseases in the near future. LBP projects focus on the development of assays for assessment and characterization of multi-strain products. Learning Objectives: You will
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associated risks to U.S. farmlands and agricultural resources. Learning Objectives: During this appointment, the participant will develop hands-on experience working within an interdisciplinary research team
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academic research through accessible media and non-media based learning platforms such as websites, webinars, newsletters, conferences, peer-review journals, and meetings for the US Forest Service and
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in injured war fighter and patients on Extracorporeal Membrane Oxygenation (ECMO). This opportunity provides you, as the faculty participant, the opportunity to learn new scientific applications