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Position: PhD position in biological data integration
Institution: Eidgenössische Technische Hochschule Zürich
Department: Institute of Molecular Systems Biology (IMSB)
Location: Zürich, Switzerland
Duties: A grand challenge in systems biology is to distil information from omics data. We are flooded with vast data on metabolites, proteins, expression, and genomes, but struggle with the inference of testable hypotheses on the underlying molecular events. In the Zamboni lab, the focus is to conceive methods for the inference of metabolic activity from static molecular data such as RNAseq, proteomics, and metabolomics. Particular emphasis is given on methods that exploit prior knowledge on molecular networks
Requirements: We are looking for a candidate who is highly motivated to work on the general topic of integrating metabolomics and RNAseq. The candidate should hold a Master in bioinformatics, computational biology, statistics, or equivalent. He/she must be experienced with the analysis of NGS data and attracted by data mining in the context of molecular networks. Familiarity with cross-omics data integration, cell biology, or cellular networks are of advantage. Most importantly, the candidate must be passionate about research and innovation. The student will be embedded in the Zurich Life Science Graduate Schooland further profit from the courses and network offered by the program
   
Text: The Institute of Molecular Systems Biology (IMSB) is in the Department of Biology at the ETH Zurich. The research groups at IMSB share the same mission: we all work to develop, apply and teach the science of Systems Biology. The laboratory of Dr. Nicola Zamboni invites applications for a PhD position in biological data integration The research group at Campus ETH Hönggerberg investigates cellular metabolism, and is particularly attracted by problems of biomedical relevance and are difficult to address because complex or technically challenging. To tackle such problems, the lab resorts to a large portfolio of methods including cutting-edge mass spectrometry (i.e. metabolomics and 13C flux analysis) and computational biology. The group has a long standing experience in developing such methods and applying them to a broad range of biological systems and questions. A grand challenge in systems biology is to distil information from omics data. We are flooded with vast data on metabolites, proteins, expression, and genomes, but struggle with the inference of testable hypotheses on the underlying molecular events. In the Zamboni lab, the focus is to conceive methods for the inference of metabolic activity from static molecular data such as RNAseq, proteomics, and metabolomics. Particular emphasis is given on methods that exploit prior knowledge on molecular networks. We are looking for a candidate who is highly motivated to work on the general topic of integrating metabolomics and RNAseq. The candidate should hold a Master in bioinformatics, computational biology, statistics, or equivalent. He/she must be experienced with the analysis of NGS data and attracted by data mining in the context of molecular networks. Familiarity with cross-omics data integration, cell biology, or cellular networks are of advantage. Most importantly, the candidate must be passionate about research and innovation. The student will be embedded in the Zurich Life Science Graduate Schooland further profit from the courses and network offered by the program. We look forward to receiving your online application including a letter of motivation, CV, transcripts and contact details of 2 referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. For further information about the institute please visit our website www.imsb.ethz.ch . Apply now
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