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Postdoc in Psychiatric Epidemiology: Linking Register and Trial Data to Study Postpartum Depressi...
closely with a PhD student and the broader project team and will contribute to the implementation and follow-up of the randomized controlled trial evaluating internet-based therapy for mothers with
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will collaborate closely with a PhD student and the broader project team and will contribute to the implementation and follow-up of the randomized controlled trial evaluating internet-based therapy
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/cognition-and-clinical-neuropsychology/ , at the Department of Psychology, University of Copenhagen. Qualification requirements The candidate must have obtained a PhD degree in mathematics, statistics
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will join an international team good command of written and spoken English is necessary. As a formal qualification, you must hold a PhD degree (or equivalent) in Allergology, Immunology, Bioinformatics
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dissemination, work planning, collaboration, work/life balance etc. Qualifications The applicant is required to be fluent in English (written and spoken), hold a PhD degree within epidemiology and have a track
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will commence in collaboration with a dedicated team of experienced researchers, lab engineers, and PhD students associated with the project, and in collaboration with researchers at partner university
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will report to the Head of Department. In your daily job, you will report to Associate Professor Lasse Sommer Kristensen. Your competences You have academic qualifications at PhD level, preferably within
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contribute to development of research grant applications. Your profile The applicants should hold a PhD in structural dynamics with focus on data-driven methods (e.g., for input/state/parameter estimation) and
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to collaborate with fellow researchers, fostering a collaborative and innovative research culture. The ideal candidate has the following skills: PhD in computational biology, bioinformatics, computer science
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contribute to development of research grant applications. Your profile The applicants should hold a PhD in structural dynamics with focus on data-driven methods (e.g., for input/state/parameter estimation) and