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processes based on mobile digital technologies increase, so do the amount and severity of cyber threats. Both defenders and attackers are now using Machine Learning (ML) and Artificial Intelligence (AI
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dissemination, and translational opportunities Job Requirements: PhD in Chemistry with a focus on computational/peptide/organic/machine learning or a closely related discipline At least one first-author
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Degree PhD Learning Sciences (alternatively Dr phil, Dr rer nat, Dr med; not recommended for international students) Course location München Teaching language English Languages Courses are held
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 26 days ago
the department and teach courses if they choose to do so. Education and Experience: Applicants should have (or expect to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in
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Location Lexington, KY Grade Level 12 Salary Range $62,400-111,634/year Type of Position Staff Position Time Status Full-Time Required Education PhD Click here for more information about equivalencies: https
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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems