53 computer-vision-and-machine-learning PhD positions at University of Groningen in Netherlands
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systems—commonly referred to as neuromorphic computing—holds the potential to create highly intelligent machines capable of supporting a wide range of everyday applications, from autonomous vehicles
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systems—commonly referred to as neuromorphic computing—holds the potential to create highly intelligent machines capable of supporting a wide range of everyday applications, from autonomous vehicles
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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spoken English. Strong analytical skills. Willingness to acquire a variety of additional skills ranging from physics modelling and statistical data analysis to hardware programming. PhD researchers
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Fully funded PhD position (1.0 FTE) with the Centre for Media and Journalism
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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, conference presentations, and ultimately a PhD dissertation. The PhD thesis is to be completed within four years. You are also requested to teach. You will work with the following supervisory team: Dr. Frank
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of diverse, deformable textiles at cycle times below one second, while hyperspectral, NIR, Raman, and RGB sensors feed an edge-compute AI pipeline for real-time decision making that routes each item
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Computational Linguistics, Argumentation Theory, and Social Network Analysis to (1) investigate how climate misinformation contributes to political polarization and (2) assess whether AI-generated, argumentative