73 web-programmer-developer "https:" "https:" "https:" "UCL" "UCL" PhD positions at Technical University of Munich
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to challenging questions in the field of computational material design, especially with the help of CALPHAD-based methods. For further development of our simulation environment (https://github.com/cmatdesign
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stimulating work environment that promotes individual creativity and effective teamwork with a clear focus on quality output. More in-formation about the group is available at http://pur.wzw.tum.de
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of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking for highly motivated and enthusiastic PhD
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of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking highly motivated and enthusiastic PhD
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for probing chemistry at surfaces and interfaces [1]. We want to strengthen this research direction by i) developing a second generation of NV-based NMR spectrometer and ii) applying it to material/energy
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–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
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work at the interface of artificial intelligence, materials science, and sustainable chemistry to develop new approaches for the recovery of rare earth elements. Rare earth elements are essential
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of extension (TV-L E13 75%) in a highly motivated team combing on equal footing experimental and theoretical research. Professional career development complementing your scientific research is offered via TUM
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focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how-to-store
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reinforcement learning methods can be used to solve multiobjective discrete and combinatorial optimization problems. The goal is to develop new algorithmic approaches that combine ideas from machine learning