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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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independently and in a structured manner. Applicants must have good collaboration skills and the ability, willingness, and commitment to work in a multidisciplinary team. Admission to the PhD programme at
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are eligible to apply. Personal skills We are looking for highly motivated and structured candidates with excellent laboratory skills and excellent collaborative qualities. The successful candidate is positive
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and in a structured manner have good collaboration skills and the ability to contribute to the development of this scientific field be able to take initiative and actively participate in the development
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English and the applicants should have an excellent command of the English language, written and spoken. Applicants must be able to work independently and in a structured manner. Applicants must have good
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structured candidates with excellent laboratory skills and excellent collaborative qualities. The successful candidate is positive-minded, well organized, looking forward to learning and developing new
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Additional preferred expertise and experience Experience with longitudinal data analysis and advanced statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural
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the top tier. This requirement also applies to the master’s thesis. Personal skills The person hired must: be able to work independently and in a structured manner have good collaboration skills and the
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statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural equation modeling). Familiarity with the opioid and endocannabinoid system and topics related
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and other forms of dissemination. An additional important task is to contribute to the establishment of a harmonised data management structure and liaison with the international partner sites and