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institutions, and leading industry partners. The successful candidate will contribute to the delivery of high-impact research projects involving AI algorithm evaluation and image data analysis. You will play a
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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work here to develop through our sector-leading Birmingham Professional programme which provides all professional services staff with development opportunities and the encouragement to reach their full
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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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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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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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their own research programme as well as support in the delivery of AI upskilling and expertise transfer to government. What you would be doing The objectives for the role are: to deliver ground-breaking
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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 for end-to-end