265 algorithm-development-"https:"-"Foundation-for-Research-and-Technology-Hellas" PhD positions
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Field
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-cases of classical supercomputers, the development of quantum CFD algorithms will be of widespread benefit upon the arrival of fault-tolerant quantum computing. This project involves the adaptation
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addresses two intertwined goals: Improving Human Training: Developing adaptive haptic training strategies that help operators refine their skills through real-time skill estimation, multimodal feedback, and
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, integrated circuit designers, and quantum algorithm developers Analyze and interpret experimental data, contributing to scientific publications, patents, and presentations. Engage with the wider international
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mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 1 day ago
the length-scales at which fibers interact, innovative approaches are crucial. Recent developments for the simulation of frictional fibers have made possible the efficient simulation of tens of thousands
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to maximise early outbreak detection. Active intervention: developing decision-making algorithms that recommend effective public-health interventions. Reinforcement learning (RL) provides a natural framework
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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students to become experts in a specific domain of choice. This vacancy is explicitly targeted at candidates interested in algorithmic biases and developing methodological approaches to tackle this challenge
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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is to develop machine-learning-based algorithms for transmitter pre-distortion and receiver post-distortion architectures that enable distortion-free quantum communication systems. A key focus will be