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Field
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr
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knowledge of quantitative methods, particularly in statistics and econometrics; experience in machine learning is a plus Background in business/management/behavioral science Experience with programming
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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implementation on IBM’s ibm_cleveland quantum computer by reproducing recently published benchmark QM/MM simulations [2] Apply the developed code to simulate proton transport in vesicular glutamate transporters
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 5 days ago
research topic, which is assigned to one of the research areas offered , also allows doctoral students to contribute their own institutional experience. A structured and international learning environment is
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written and spoken English skills High degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very
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science (for example, but not limited to, data science, machine learning, statistics, computer science, mathematics, etc.) acceptance by a PhD supervisor with examination admission for PDS and formation
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profile is shaped in particular by five high-profile areas. About Minds, Media, Machines Minds, Media, Machines (MMM) is one of the five interdisciplinary, high-profile areas that largely define