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Field
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uncertainty quantification. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and
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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415
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invites applications for a Post-Doctoral Associate position, in the area of Quantum Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects
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outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision
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hold, or are close to completing, a PhD in robotics, robot learning, or a closely related field. You possess strong expertise in deep learning and robot navigation, with hands-on experience in deploying
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, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing
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will develop algorithms and methods aimed at better detection and mitigation of GNSS interference events from either jamming or spoofing attempts. In addition to research within GNSS integrity
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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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limited to artificial intelligence, computing theory (algorithms, complexity), data science, statistics, discrete mathematics (graph theory, combinatorics), game theory, machine learning, optimization