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<b style="caret-color: rgba(0, 0, 0, 0.87); color: rgba(0, 0, 0, 0.87); font-family: Roboto, RobotoDraft, Helvetica, Arial, sans-serif; font-size: 14px">Open 4-year fully funded PhD position in the<span class="Apple-converted-space"> </span><a href="https://machine-learning.uit.no/" target="_blank" rel="nofollow" data-saferedirecturl="https://www.google.com/url?hl=en&q=https://machine-learning.uit.no/&source=gmail&ust=1599895799439000&usg=AFQjCNEFEBX_OVbL5iZXxmtk9uogZYtekA" style="color: rgb(26, 115, 232)">Machine
Learning Group</a><span class="Apple-converted-space"> </span>at UiT The Arctic University of Norway.</b><br style="caret-color: rgba(0, 0, 0, 0.87); color: rgba(0, 0, 0, 0.87); font-family: Roboto, RobotoDraft, Helvetica, Arial, sans-serif; font-size: 14px">
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We are seeking a PhD Fellow to take an active role in the group's research on developing novel machine learning methodology for prediction of targets overrepresented in the genomes of problematic antimicrobial resistant bacteria. <b><br>
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We are particularly seeking a candidate that has a machine learning background and is familiar with traditional techniques such as random forests and linear regression (for instance, Lasso and elastic nets) as well as deep learning.<br>
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The successful candidate will join the UiT Machine Learning Group, a vibrant group at the "north pole", with excellent national and international connections. <br>
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For details, please see: <a href="https://www.jobbnorge.no/en/available-jobs/job/191963/phd-fellow-in-machine-learning-for-antimicrobial-resistance" target="_blank" rel="nofollow" data-saferedirecturl="https://www.google.com/url?hl=en&q=https://www.jobbnorge.no/en/available-jobs/job/191963/phd-fellow-in-machine-learning-for-antimicrobial-resistance&source=gmail&ust=1599895799439000&usg=AFQjCNE1PFIOsaScgTz_lNrtHvqcBEF94w" style="color: rgb(26, 115, 232)">https://www.jobbnorge.no/en/available-jobs/job/191963/phd-fellow-in-machine-learning-for-antimicrobial-resistance</a><br>
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Please contact me (michael.c.kampffmeyer@uit.no) for more info. </div>
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Best,</div>
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Michael</div>
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