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Field
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approaches are gaining importance for autonomous vehicles. However, the training and certification of autonomous systems with machine learning components is a huge challenge, since the learned behavior is
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Methods in Magnetic Resonance Spectroscopy and Imaging. Project topics include: Steady-state free-precession (SSFP) techniques that improve resolution and sensitivity NMR spectra and MRI images; Spectral
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processes, as appropriate, using a variety of methods and techniques and to provide effective, timely and appropriate feedback to students to support their learning. 4. Supervise individual student projects
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resonance spectroscopy, imaging (MRI), Applied Mathematics or Machine learning. We are looking for talented, highly-motivated experimentally skilled young scientists with Master degrees or equivalent or PhD
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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vision, machine learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100
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evaluation of publications in ISI/SCOPUS journals: in advanced statistical models (e.g., Machine Learning), as well as in programming skills, data collection and processing, particularly from drone-captured
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate