252 machine-learning "https:" "https:" "https:" "https:" "https:" "Dana Farber Cancer Institute" Postdoctoral positions at Nature Careers
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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Aarhus University (http://bio.au.dk/en) and work in the Archaea Group (https://bio.au.dk/en/research/research-areas/microbial-processes-and-diversity/archaea-group), Section for Microbiology
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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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computational approaches for high-dimensional data analysis. https://www.epelmanlab.com/ http://www.uhnresearch.ca/researcher/slava-epelman @EpelmanLab This role has direct mentorship and guidance in grant
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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project aimed at advancing our single-cell ribosome profiling technologies in cancer. For further information about the lab, please visit https://www.sendoellab.org/. The Institute for Regenerative Medicine
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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University is committed to fostering gender equality in research and encourages women to apply. Scientists at risk are encouraged to apply. How to Apply Application website: https://cuni.cz/UKEN-2187.html
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mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us