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p.a. plus 17% super (retirement savings system/pension scheme) Unravel molecular mysteries in bat wing development / Collaborate with renowned experts / Shape the future of evolutionary biology. Apply
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must hold a PhD, or be near to submission of a PhD, in a relevant field of Microbiology or Evolutionary Genetics, ideally involving Fungal Biology. They must understand microbial laboratory practices and
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extend their research portfolio. Candidates must hold a PhD, or be near to submission of a PhD, in a relevant field of Microbiology or Evolutionary Genetics, ideally involving Fungal Biology. They must
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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the Francis Crick Institute. This initiative brings together world-class experts in evolutionary genomics, stem cell biology, and computational science to unravel one of the most fascinating puzzles in
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arrangements. Are you interested in cellular and genetic responses to climate change? Do you have an established background in molecular aspects of evolutionary ecology or development? Do you want to further
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. This role will contribute the development of novel machine learning algorithms for wireless sensing and communication and the proof of concepts for next-generation wireless communication, collaborating with
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. The post is part of the project that aims to develop digital twin frameworks within the Wind Energy sector with novel AI predictive maintenance algorithms for fault-tolerant, intelligent estimation
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work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through
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resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge on control is highly preferred. Have experience and commitment to supervising student