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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now
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will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be advantageous. Proficiency in algorithm development using Python will be advantageous
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an active role in data management, processing, and quantitative analysis (e.g., longitudinal and multilevel modelling, time-series or high-frequency data analysis, machine learning or predictive
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methodologies Experience with machine learning techniques Experience with pipeline development and testing (gitlab, simulated light curves…) Ability to work independently and to collaborate in an international
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holder must have: Expertise in advanced theoretical and computational electromagnetics, including high frequency asymptotics. Expertise in artificial intelligence and machine learning. Recent research
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• A comprehensive range of childcare services • Family leave schemes • Cycle and electric car loan schemes • Employee Assistance Programme • Membership to a variety of
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. Preference will be given to those with a relevant portfolio related to system development, human-computer interaction or cultural studies, and/or with knowledge of Cantonese. Applicants are invited to contact
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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or an equivalent qualification. For all posts, applicants should also: (a) have solid experience in electric machines, finite element methods and theory of electromagnetic files; and (b) be able to complete