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Field
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regular gatherings such as research group professional meetings, weekly colloquia, shared lunches, and “Friday coffee” sessions to end the week. These formal and informal events offer opportunities to share
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friendly, supportive atmosphere, with regular gatherings such as research group professional meetings, weekly colloquia, shared lunches, and “Friday coffee” sessions to end the week. These formal and
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vulnerabilities and devise static and/or dynamic approaches to detect them in the code or prevent their execution at runtime. The focus will be on a fuzzing approach in a Java/Android environment. Keywords
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development knowledge (such as HTML 5 or Java) for front-end integration and data visualization is an added value. All candidates are strongly encouraged to submit their Master’s thesis and/or any other
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programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin. Instructions
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Computer Science, Medical Informatics, Business Informatics, or a related discipline Knowledge of database systems, data integration, and data warehousing Programming skills, ideally in Java and/or Kotlin Interest
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skills (mandatory): Strong understanding of sustainable AI or related areas Experience of programming in Python / C / Java or equivalent Experience with using Machine Learning software, e.g. PyTorch
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include a thesis of at least 30 ECTS. Fluent oral and written communication skills in English. Documented programming skills in a relevant language (e.g. Matlab, LabVIEW, Java, C++, IgorPro). Must be
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, and “Friday coffee” sessions to wrap up the week. These formal and informal occasions provide opportunities to exchange ideas, celebrate milestones, and strengthen connections. PhD candidates also
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working environment is characterized by a friendly, supportive atmosphere, with regular gatherings such as research group professional meetings, weekly colloquia, shared lunches, and “Friday coffee