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causal relations between genetic alterations and disease 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
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of cellular networks hampers our ability to establish causal relations between genetic alterations and disease phenotypes. In this PhD you will address this by a deep learning model of drug responses in cancer
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proteomics methods in a clinical setting. The PhD student will be part of a multi-disciplinary team consisting of experts in cancer biology, proteomics, bioinformatics as well as lung oncology. Within
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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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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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. The doctoral student project and the duties of the doctoral student This PhD project consists of both statistical methodology development and clinical application in the field of population-based cancer patient
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. The doctoral student project and the duties of the doctoral student We have a four-year full-time position as PhD student in our research group in Karolinska Institutet available to study childhood cancer in
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of the doctoral student The doctoral student will focus on projects to characterize mechanisms of immune regulation in patients with non-small cell lung cancer undergoing immune checkpoint therapy. The project
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the understanding of causes and consequences of health and disease, with a focus on neurological and neurodegenerative diseases, psychiatric disorders, and cancer. We strive to, through multidisciplinary approaches