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costs, and tightly bridge the gap between software and hardware design. As a doctoral student, you will work on developing a framework that connects new learning algorithms with their physical
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, mathematics, data Science or related disciplines with a proven track record of expertise/expertise in tool and algorithm development and/or applied bioinformatics, who are also keen to expand our research
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Supervisors: Prof. Finn Werner – Werner Lab Website Dr. Christopher Waudby – Waudby Lab Website Abstract: RNA polymerases (RNAPs) are essential enzymes for viral replication and represent
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algorithms to ensure seamless, reliable, and secure wireless communication in challenging and dynamic environments. The key responsibilities for this positions are listed as the following: Develop protocols
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[Wissenschaftszeitvertragsgesetz, WissZeitVG]).Application deadline: 16.12.2025Scope of work: full-time position suitable for part-timeThe goal of this project is to develop and analyze application-oriented benchmarks for Rydberg
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programming skills. Expertise in developing computer vision and machine learning algorithms would be desirable, highly motivated and enthusiastic about advancing AI for societal impact. Qualifications A high
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by: Developing specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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and dynamics, which we also plan to investigate using AI-based pattern recognition algorithms. In this project, the PhD student will: Run the MIT General Circulation Model (MITgcm) together
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in the network. Here unfair indicates that people with different personal traits are differently and unjustly affected by algorithms not designed to consider those traits. This project aims to develop