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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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Internal Number: 7071018 Postdoc Research Associate Job Identification: 20071 Posting Date: 04/09/2026, 08:03 PM Job Schedule: Full time Locations: 101 Bagby Avenue, Waco, TX, 76706, US Degree Level: Job
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and geometric deep learning, or simulation-based inference. We welcome your unique perspective and are eager to learn how your track record, educational vision, and future research goals align with
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The VCC center at KAUST is looking for research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep learning. A suitable candidate
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algorithms as well as deep learning workflows on GPU servers (use of Git, Docker, and PyTorch) Design, implementation, and evaluation of spatial proteomics and multiplex analyses for characterizing the tumor
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17 Apr 2026 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Computer science Researcher Profile Recognised Researcher (R2) Positions Postdoc
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Job Description The Administrative Specialist is responsible for developing a deep understanding of the academic and research programs of the AI & Machine Learning for Engineering Graduate Programs
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
. Throughout the Fellowship, individuals will have the opportunity to participate in research using digital pathology, machine learning, deep learning, artificial intelligence, and digital image analysis. Other
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neurological disorders, novel applications of deep brain stimulation technology to the treatment of neurological and psychiatric disease, the mechanisms of deep brain stimulation and finally motor and reward
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deep experience with PyTorch, JAX, or TensorFlow. Broad knowledge of modern ML and optimization (gradient‑based, evolutionary, Bayesian, reinforcement learning). Hands‑on experience with generative