33 learning-"https:" "https:" "https:" "https:" "https:" "https:" "https:" PhD positions in Sweden
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perform both empirical and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in
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willingness to learn Swedish. A valid driving licence. Personal qualities, including curiosity, initiative, reliability, organisational ability and willingness to collaborate, will be important in the selection
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analysis. Experience of statistical analysis in R. Knowledge of Swedish or another Scandinavian language, or a willingness to learn Swedish. A valid driving licence. Personal qualities, including curiosity
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, or DNA-based analyses. Experience of ecological or statistical data analysis. Knowledge of Swedish or another Scandinavian language, or a willingness to learn Swedish. A valid driving licence. Personal
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, or by agreement. The main language of the PhD program is English. However, non-Swedish speaking students are expected to acquire basic skills in Swedish during the period of employment
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acquire the doctoral education. Good English communication, including an ability to clearly disseminate research findings orally and in writing, are essential. Additional qualifications Selection will be
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and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in scientific journals
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the student to progressively acquire knowledge in scientific methodology, experimental research, data analysis, and scientific communication. As part of your doctoral studies, your duties will include
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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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for latent variables and their connections to modern machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates