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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements PhD degree in machine learning, automatic control, system identification, signal processing
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productivity software (e.g., MS Office), and ability to operate standard office equipment (copy machine, fax machine, multi-line phone). Applications are being accepted on line at https://unmc.peopleadmin.com
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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required as the research progresses. Position Status Full Time Posting Number 26FA0362 Posting Open Date Posting Close Date Qualifications Minimum Education and Experience This position requires a PhD or
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Computer Vision and Generative AI. The successful candidate will join a dynamic research environment and contribute to cutting-edge research at the intersection of computer vision, generative artificial
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funding. The start date is 1 September 2026. The appointee is expected to reside in the Helsinki Metropolitan Area during the employment. QUALIFICATIONS AND EVALUATION Applicants are required to hold a PhD
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of their effective start date. This position is for a post-PhD trainee preparing for a research scientist career path. The planned position will provide a transition to career independence through
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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We are seeking to recruit a 2-year postdoctoral researcher within Human-Computer Interaction to work on the interdisciplinary project DARES: Data Quality for Responsible AI in Energy Systems funded
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze