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. Preferred Qualifications Experience with: C/C++, Python, MATLAB, ROS 1 and 2, OpenCV, Unity, GPU programming, linear and nonlinear control theory, supervised, unsupervised and reinforcement learning, Torch
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of the planning and implementation processes with emerging energy technologies. You will develop and execute trainings and workshops for practitioners based on theories in Environmental psychology and empirical
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of the tissue microstructure. In this position, you will work on developing advanced preclinical MRI techniques and you will employ them for 1) in-vivo mouse liver imaging, both for normal controls and in models
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activity patterns being associated with movements and others not. By using our novel techniques, that can drive precise patterns of activity distributed across many neurons, we can test different theories
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proposals to existing and prospective sponsors. Knowledge, Skills and Abilities: Knowledge on theory on free space optical communication, air turbulence and adaptive optics correction. Familiarity with
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application of engineering principles, theories and concepts as well as general knowledge of hybrid energy related disciplines and applications. The researcher will use a combination of conventional control
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analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about
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scholarship is an ideal starting point for someone wishing to establish a future cross-disciplinary research lab that integrates theory and experimental research. Specific Qualifications for Project A
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foundations of deep learning, functional analysis and measure theory. You can find more information about our research area and our team on the website: http://www.olgamula.com. As a team, we understand the
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of the tissue microstructure. In this position, you will work on developing advanced preclinical MRI techniques and you will employ them for 1) in-vivo mouse liver imaging, both for normal controls and in models