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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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Description Within the ANR HEBBIAN contract, the objective is to adapt bio-inspired Hebbian learning models recently proposed by one of the partners of this ANR (Frédéric Lavigne) in order to account for data
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scientific capacity in the region. The candidate will also lead NYUAD’s annual Southeast Asia Learning Exchange, an immersive week long program that brings regional researchers to Abu Dhabi for advanced
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the support of and under the supervision of a Principal Investigator. To become familiar with the publication process. To acquire generic and transferable skills (including project management, business skills
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. To acquire generic and transferable skills (including project management, business skills and postgraduate mentoring/supervision). To engage in the wider research and scholarly activities
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environment? If so, the Oak Ridge National Laboratory’s Learning Systems Group within the Data and Artificial Intelligence Systems section invites you to apply to our new postdoctoral research associate
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
join forces to push the boundaries of data‑driven discovery. Our mission is two‑fold: to advance fundamental theory in probability and machine learning, and to translate those breakthroughs into high
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the research activities entrusted to the officer take place: This ANR project lies at the interface between statistical learning (mainly deep learning) and combinatorial optimization (mainly stochastic and
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communication skills; ability to work effectively in an international environment. • Demonstrated ability and motivation to learn new techniques and procedures. • Experience with control and data acquisition
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approaches beyond standard deep learning methods. Demonstrated experience in academic research (e. g. through publications, conference contributions or comparable scientific achievements). Very good