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Field
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State programme promoting young researchers (Tenure-Track Programme). The professorship is affiliated with the department of Medical Systems Biology (https://www.med.uni-wuerzburg.de/en/systemimmunologie
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University degree in data science, computer science, information science, computational ecology, statistics, or equivalent Competence in Python, R or other relevant programming languages (knowledge of LabView
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of Expertise: Apply your physics knowledge to create functional program code. Quality Assurance: Fix bugs in the existing code. Documentation: Create and maintain documentation for your work. Team Coordination
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or cognitive science or related Programming skills, particularly in Python (including interface integration) Experience with handling LLMs (e.g., GPT-4) and their API interface Basic knowledge in Natural Language
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languages used: C++ 2014, CUDA, Lua Desirable: - interest in high-performance computing with graphics processors (GPUs) and simulation methods - fluent knowledge of modern C++ and a scripting language
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program in computer science, electrical engineering, mathematics, or a comparable field of study Good knowledge of the Python programming language Solid knowledge in at least one of the following areas
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-based control technology as well as knowledge of other programming languages (e.g., C, C++, or Java), but this is not a requirement. So do not worry if you do not have all those skills just yet, you can
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Performing requirement analyses together with laboratory staff and backend developer Software support for development projects in the laboratory Your profile Completed university degree in computer science
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across five departments—Physical Oceanography, Marine Chemistry, Biological Oceanography, Marine Geosciences, and Marine Observations—in an interdisciplinary framework as part of a joint research program
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in Bioinformatics, Computational Biology, Biostatistics, Data Sciences or related discipline. Alternatively, PhD in Molecular Biology, Immunology, Biomedicine or related discipline with extensive