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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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operation of the umFm module unit used in vertical farm which includes handling of soil compost, irrigating of the crops and taking note of the sensors incorporation in the vertical farm inhouse. Job
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) The University of Strathclyde has a significant depth of space research expertise across its Applied Space Technology Laboratory, the Sensor Signal Processing & Security Laboratory, and the Aerospace Centre
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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algorithms might support the wider integration of, and uptake of, renewable energy technologies for particular use cases and considering a variety of perspectives (technical/policy/social/economic). You will
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include but are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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an ingestible pill sensor for early detection and diagnosis of metal disorders. This EPSRC funded post is available immediately. The successful applicant will support the translation of an AI-enhanced capsule
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, the appointed candidate will work closely with the line manager to develop novel control algorithms in EAP soft robotics combining Gaussian Predictors, hands-on laboratory experiments and JULIA computing
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Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search