408 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nature Careers in United States
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, military branch, conflict counselling). Experience in data entry and working in emergencies and fast pace, stressful environment. Some experience with computer systems, including Microsoft Office (Word
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(EHR), health information exchanges, and data analysis software. Experience with health IT innovation, including working with artificial intelligence, machine learning, telemedicine, or mobile health
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(such as a laptop computer or tablet). Work may involve possible exposure to malodorous vapors, low dose radiation, contamination by toxic chemicals and acids and presence of carcinogenic substances or other
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collecting relevant data from 2D, 3D or 4D images. Perform computer automated analysis and quality control on large data sets. Liaise effectively with other groups at Janelia to manage multiple image analysis
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to integrating computational simulation, data science, and deep learning technologies to deeply explore structure–property relationships in materials. Its goal is to drive the precise design and development of new
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research. Initially, jET interns will be dedicated to learning engineering tools and best practices by assisting staff engineers and scientists in ongoing work. Later on, jET interns will be expected to work
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diseases, using primary hematopoietic graft products and genetically modified products for sickle cell disease and CAR T-Cell therapy applications. The Human Applications Laboratory is composed of two
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positive and collaborative working environment. Foster innovation in teaching and learning by supporting faculty in pedagogical advancements and instructional technologies. Student Engagement and Success
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current with the latest literature in chemical and chromatin/cancer biology is highly desirable. If you're passionate about scientific discovery and eager to learn in cancer biology, we invite you to apply
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for developing and implementing new informatics tools and resources to enhance phenotyping performance or enable deep phenotyping through terminology/ontology, natural language processing, and machine learning