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(postdoc) Reference no.: 5955 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about
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, perform, troubleshoot, and interpret experiments. Ability to rapidly learn, optimize, and implement new or advanced assays as required by the evolving research direction. Experience leading or substantially
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English sufficient for professional communication, working with scientific literature and preparing scientific publications. Ability to work effectively in a team, independence, accuracy and willingness
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expertise and initiative through international publications in peer-reviewed journals Experience in research management Didactic skills and experience in e-learning Good IT skills Excellent knowledge
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data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
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The Pluskal lab at IOCB Prague combines cutting-edge experimental (e.g., LC-MS, metabolomics, RNA-seq) and computational (e.g., bioinformatics, molecular networking, machine learning) approaches
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, molecular and outcome data available (e.g., survival, cancer recurrence, response to treatment, etc.). BENEFITS: We expect this framework to learn, discover and deliver novel biomarkers that can improve the
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Liturgical Studies (and Sacramental Theology) or on a relevant liturgical topic (Ph.D./STD/Dr.theol.), Excellent written and spoken English, Teaching experience, Experience with e-learning, Experience
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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
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programmatic activities such as seminars, workshops, and collaborative research initiatives. Develops methodologies and tools for use in the electronic medical records that will strengthen the Learn Health