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Field
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methods Good knowledge of object orientation and at least basic knowledge of UML Knowledge of minimum one programming language (e.g. C++, Python, Java) Experience with the Robot Operating System (ROS) Good
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, Creativity, Motivation towards Research. - Interest in interdisciplinary sciences and research. - Excellent programming skills in one of the following languages: C/C++, Python, Java, or R. - Fluent spoken and
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skills (Python, R, Java, …) and interest to work in polyglot software environments Practical experience with machine learning and AI methods and an interest to learn, adapt and apply ML methods
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(e.g. Python, R) or a universal programming language (e.g. C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills (written and spoken) High
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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
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on tropical value chains (cocoa, coffee, tea, palm oil, banana, etc.) and conducting research supporting the private sector with their monitoring, evaluation and learning is a must. You should have excellent
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regular gatherings such as professional meetings within the research group, weekly colloquia, shared lunches, and “Friday coffee” sessions to end the week. These formal and informal events offer
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, respectful, diverse and international. Good coffee, for free. Or tea, if you prefer it. The opportunity to build a broad national and international network of scientific and industrial partners, and develop
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) computer science or a closely related field; Demonstratable expertise in quantum computing; Good programming skills in C/C++ or Java; Proficient in spoken and written English; An independent and creative team player
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, Management Science, Analytics and Data Science Knowledge of and practical experiences with programming (e.g., Python, Java, Julia, etc.) You must have a two-year master's degree (120 ECTS points) or a similar