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datasets Working with bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq, methylome and proteomic data. Developing computational approaches and algorithms to answer complex biological questions. Identifying
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technical elements of computational astrophysics research, which may include but are not limited to: algorithm and software development; application or development of computational or statistical methods
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and machine learning algorithms to analyse and interpret the acquired data. The successful candidate will work primarily with Dr Qimei Zhang in the Department of Engineering at the Nottingham Trent
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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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these connected directions. Research will emphasise new learning algorithms and rigorous evaluation using public datasets, simulation and, where available, robotic and edge-computing platforms. Evaluation will
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software development and scientific computing algorithms as well as the ability to learn quickly. Candidates will be evaluated solely on their ability to demonstrate the skills, knowledge, and experience
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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perception, mapping, obstacle avoidance, and multi-agent path-planning algorithms, and integrate these capabilities on physical drone platforms. The work will involve system integration, simulation, hardware
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dementia identification algorithms. This position is ideal for candidates with strong quantitative skills who are interested in aging, Alzheimer's disease and related dementias (ADRD), social determinants
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems