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such as type 2 diabetes and cardiovascular disease. Our group consists of 15-20 members (senior researchers, postdoctoral fellows, PhD/master students, and technical staff) and has all the necessary
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phenotypes. In this PhD you will address this by a deep learning model of drug responses in cancer. The PhD position focuses on predicting cell type-specific drug responses, identifying transcriptional
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for classification of lung cancer subtype based on the generated MS-data. Finally, the student will evaluate the applicability and value of the developed clinical proteomics methods in a clinical setting. The PhD
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completed degree are met before the (intended) date of employment. This must be substantiated by the applicant's main supervisor, director or equivalent. The candidate should have obtained a PhD degree in
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You meet the general eligibility requirement for doctoral/third-cycle/PhD education if you: have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or have satisfied
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geneticists, psychologists, psychiatrists, and statisticians. The group is based at the Department of Medical Epidemiology and Biostatistics, where the the Phd student will also work. The doctoral student
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) General eligibility requirement You meet the general eligibility requirement for doctoral/third-cycle/PhD education if you: have been awarded a second-cycle/advanced/master qualification (i.e. master degree
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collaboration skills are important, including assisting PhD students and postdoctoral researchers at the unit with their projects and helping with the introduction of new team members. Eligibility requirements It
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murine models of cancer. The applicant is expected to have a strong interest in senescence and cancer. The applicant will work in close collaboration with other PhD students, postdocs and researchers
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guidance to doctoral students and teaching master’s or doctoral-level courses The position also involves other tasks within the projects. Eligibility requirements We are seeking a skilled, motivated, and PhD