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in computer science, engineering, data sciences, applied mathematics, machine learning, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at
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for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in English The
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departmental duties, up to a maximum of 20% of full-time. Your qualifications You have a Master’s degree in electrical engineering, engineering physics, computer science, applied mathematics or have completed
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, engineering physics, computer science, applied mathematics or have completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses within the topics mentioned above
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competence in System Analysis including Environmental Systems Analysis and LCA, as well as Biometrics (statistics and mathematics with applications in biological systems) and Automation and Logistics. Read
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to postgraduate education is a person who has completed a degree at an advanced level in a technical, mathematical, or scientific field or who has otherwise acquired knowledge to be able to benefit from
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sampling, forest mathematical statistics and landscape studies. The department is also responsible for the implementation of the ongoing environmental monitoring programs the National Forest Inventory
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Do you want to contribute to improving human health? To be a doctoral student means to devote oneself to a research project under supervision of experienced researchers and following an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is...
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, the student must have satisfactorily undertaken courses in Mathematics equivalent to at least 30 ECTS credits. The assessments of the applicants are based on their qualifications and their ability to benefit
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of mathematical modeling and data analysis. Experience of programming languages and tools commonly used in biophysical or agricultural modeling (e.g., Python and R). Familiarity with food system resilience