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a part of the life of a vibrant and active college campus. To learn more, go to Baylor Benefits & Advantages. Explore & Engage Learn more about Baylor and our strategic vision, Baylor in Deeds
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Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and to innovate
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University of California, San Francisco | San Francisco, California | United States | about 6 hours ago
agreement. The salary range for this position is $167,800 - $251,700 (Annual Rate). To learn more about the benefits of working at UCSF, including total compensation, please visit: https
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commits the University to the bold ambition to be a global leader in dual sector learning and research by 2028. We are currently developing a Centre of Excellence in Paramedicine at our St Albans Campus
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for a pool of qualified Part Time Faculty to teach courses in a variety of disciplines across all 10 colleges and schools. Individuals may enter expressions of interest by submitting their credentials
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cellular reprogramming strategies and identify new omics-based biomarkers. We work closely with clinical partners and we focus on deep understanding of molecular mechanisms of disease development. PhD
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to stay at the forefront of medical science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater
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++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both independently and collaboratively Experience with deep learning frameworks, such as
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Faculty Salary Schedule: https://www.gavilan.edu/jobs/salary/docs/Faculty-Salary-24-25.pdf Assignment Start Date: Fall 2026 Semester About Gavilan: Located in the heart of California between San Jose and
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disciplines associated with geography, soil sciences, hydrology, civil engineering, or related discipline, with research expertise in geospatial AI, deep learning foundation models, hydrology, river science