353 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship research jobs
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collocates Hawkes (formerly CMIC), UCL’s AI Centre (AIC), and UCL’s Advanced Research Computing Centre (ARC) creating a vibrant hub of data-science researchers with interests from basic machine learning and AI
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning
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modeling, machine learning methods, and applications involving text and other non-traditional data sources. The fellow will contribute to and extend research in these areas, engaging in projects that develop
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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Website: https://engineering.uark.edu/ Summary of Job Duties: The Postdoctoral Fellow will continue investigation of cancer nerve crosstalk in both breast cancer and pancreatic cancer. In both projects
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fields. Relevant Training or Courses (optional): Experience with R or similar programming tools, or machine learning algorithms. Geographic Information Systems (GIS). Basic and advanced statistics, time
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per year. The successful candidate will be able to teach Introduction to Comparative Politics, in addition to an intermediate-level European politics course and a thematic course in a more specific area
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Engineering/ Electrical Engineering. 2. Admission Requirements: Bachelor's degree in Computer Engineering, Systems and Information Technologies Engineering, Electrical and Computer Science Engineering, or in a
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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R