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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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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
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Science; Have knowledge of SQL, Python, ArcGIS, Power BI, Java, and SAS. Work plan and goals to achieve The work focuses on developing an Integrated Analytical Platform for Territorial Intelligence – Smart
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skills and programming experience, preferably in R and C++ (or Python, Java or similar); clear interest in the field of biomedical or public health research; good communication skills and excellent command
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data integration data quality data analytics programming languages (SQL, Python, Java) Complementary IT skills: machine learning image recognition sensor technologies robotic technologies
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-domain context. Good knowledge of programming languages (e.g. Python, R, Java, C#, C++) Good knowledge of object orientation and at least basic knowledge of UML Knowledge in the field of machine learning