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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
to completion) relevant to empirical modelling (any discipline), machine learning (any discipline), inverse methods (any discipline), ionospheric modelling and/or ionospheric measurement techniques, radio
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systems to rapidly traverse evolutionary landscapes Evolution of complex, multi-gene phenotypes Engineering plug-and-play selection systems for continuous evolution of diverse phenotypes Learn more at How
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broad implications for how we understand and engineer life. Learn more at How to apply Applications will be reviewed on a rolling basis. In your cover letter, please clearly explain your fit, interest
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of their career. The Career Development Fellowships will enable early career academics to acquire a strong and well-rounded foundation to support future applications for substantive academic roles at Durham
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genome synthesis and artificial intelligence will enable biological design at the organism scale with implications in bioproduction, human health, agriculture, and beyond. Learn more at jzlab.bio How
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towards better understanding what replication can mean for qualitative research. Last but most topically, the theme of replication raises a host of questions in relation to machine learning and artificial