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(pre-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models; integration and analysis
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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into actionable insights, novel tools, and impactful research outcomes. Key Responsibilities Develop, implement, and optimise AI/ML models (artificial intelligence/classical machine learning, deep learning
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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seminars, MA seminars and/or specialist classes. The selected candidate is expected to teach courses on topics in the field of quantitative finance, machine learning and data science. Courses should be
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like knowledge graphs, information extraction, machine learning or artificial intelligence in the context of scholarly data Publication of research and project results Your profile: Scientific University
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education/experience combined) Required License Yes If yes, what is the required licensure/certification? Valid Driver’s License Required Computer Applications: Not Applicable Required Other Computer
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. (Will consider eight years related education/experience). Required License Yes If yes, what is the required licensure/certification? Valid driver’s license. Required Computer Applications: Not Applicable
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
(SHRA) Position Title UTS - Temporary Computer Technician- Inspection and Customer Support at UNC Chapel Hill Position Number Vacancy ID S026725 Full-time/Part-time Full-Time Temporary Hours per week Work