16 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " PhD positions at University of Amsterdam (UvA)
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supervision signals (e.g., labels in a downstream task or symbolic constraints). You will perform machine learning research, developing a framework for learning interpretable and robust concepts with
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, mathematicians, computer scientists, linguists, musicologists, and cognitive scientists, who share a fascination with the interdisciplinary study of information. This is what you will do Neural approaches
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your work is inherently collaborative. You will spend a dedicated time at the Amsterdam Medical Center (AMC) with Prof. Ed van Bavel. There, you will learn to perform blood flow perfusion experiments in
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below will be considered. Where to apply Website https://www.academictransfer.com/en/jobs/359451/phd-position-in-theoretical-par… Requirements Additional Information Website for additional job details
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experience in teaching, in particular supervising bachelor’s and master’s theses. What do you have to offer You are: Curious and eager to learn Enthusiastic about engaging with young children and their
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of theoretical computer science researchers in Amsterdam (https://theory.amsterdam ). What are you going to do? You are expected to: carry out original research in the field of theoretical computer science; have
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to a quantum computer. Given the near-term deployment of quantum computing technologies, the time to deploy post-quantum secure cryptography is now. Further, in a world with quantum computers, one can
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of (translational) neuroscience and applied physics and biomechanics, contributing to a project with major implications for health prevention in groups at high-risk of TBI, such as athletes and military personnel
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interest in interdisciplinary research at the intersection of AI and neuroscience (NeuroAI), and human vision; A background in machine learning, deep learning, and/or representational alignment research
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differences in learning, memory, and processing between these systems. This project develops the necessary methods to study how smart AI-models are compared to people, now and in the future, and sheds light on