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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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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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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
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and able to manage your priorities. 🎓 We are looking for people with a PhD in machine learning, deep learning, data science, computer science, obtained less than 3 years before the date of hire, with a
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. Disseminate research through high-impact publications and conference presentations. Requirements: PhD (or near completion) in Imaging Science, Computational Biology, Bioinformatics, Machine Learning, Data
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 28 days 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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for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Appointing a postdoctoral scholar with expertise in causal inference, machine learning, and
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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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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning