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Field
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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic
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the project will be carried out. Your qualifications You have graduated at Master’s level in machine learning, computer science, or a related area that is considered relevant for the research topic
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, mathematical and programming contexts Your research will include extending and contributing to models and codes, including both high- and low-level programming languages, e.g. Python/Matlab to the development
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master's degree in agricultural or environmental economics, applied mathematics, or a related fieldGood background in bio-economic modelling, CGE modelling, and optimization techniquesExperience with
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. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental
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higher education credits in the subjects of physics, computer science, mathematics, mathematical statistics, or related areas, of which at least 30 credits must be at the advanced (master's) level. Courses
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, sustainability science, geography, or a related field. You have experience with quantitative research methodologies, including mathematical programming or scenario modelling. You have experience with spatial
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degree in computational engineering, mechanical engineering, computer science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural
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Your profile Master's degree in computer science, Mathematics, Applied Mathematics, Computer Engineering, Software Engineering, Data Science, Information Systems (Engineering), or related fields with a
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genetics. With guidance and supervision from both experimental and computational perspectives, this program is ideal for graduates in fields such as molecular biology, biochemistry, mathematics