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hypotheses. This is a fantastic opportunity to contribute to world-class science in a leading biotechnology company. Who you are: Candidates must have a PhD in Computational Biology or Computational Science
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Computer Science, Mathematics, Physics, Applied Economics, or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning frameworks. Proficiency in
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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College of Engineering, Design and Physical Sciences Location: Brunel University of London, Uxbridge Campus Placement: Fixed term (12 months), Full–time, up to £40,757 per annum Brunel University
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about to submit) a PhD in Physics, Mathematics, Computer Science or related discipline in the Physical Sciences. No prior knowledge of biology is required but willingness to work at the interface
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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meet the following essential criteria: Have or about to obtain a PhD degree in Computer Science, Computational Biology or other relevant discipline (*must be obtained within 3 months of commencement of
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PhD Research Fellow in reservoir physics (CCS): Sealing properties of CO2 hydrate in sediments Apply for this job See advertisement UiB - Knowledge that shapes society Through robust and close
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computer science, engineering, mathematics or physical sciences area Recent high quality research experience in machine learning/AI, or both, as evidenced by a strong track record of publications in leading
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 hour ago
bring: PhD in bioinformatics, computational biology or a related field. Experience or interest in applying computational methods to RNA/mRNA therapeutics. A demonstrated ability to publish high-quality