150 machine-learning-"https:" "https:" "https:" "https:" "https:" positions at Nature Careers
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. Interdisciplinary research is actively promoted by the Faculty of Science, fostered under the University-wide six Interdisciplinary Labs (https://interdisciplinary-research.hkbu.edu.hk/), and supported by state
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and/or Drishti software packages for reconstructing CT data. Basic knowledge about machine learning is of advantage. Very good English skills. High motivation to strive for scientific excellence and to
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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong
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Research Institute at VTC (FBRI - https://fbri.vtc.vt.edu/ ) for a tenured or tenure-track faculty position at the associate or full professor level. The PRC initiative has received substantial funding
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technologies that strengthen infrastructure and improve quality of life • Supercomputing, AI, machine learning, robotics, and human–machine interaction while examining ethics, equity, and privacy in emerging
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team member in the CBSC focused on ligand discovery, joining a team of dedicated computational researchers with diverse expertise ranging from structural bioinformatics to machine learning and AI. Your
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research group is
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular