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Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic
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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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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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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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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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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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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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ecology, and forest management. Required skills and qualifications - Applicants must hold a Master's degree or an engineering degree. - The candidate should have strong skills in programming (e.g. Java