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implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Utilize PyTorch to train and fine
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. The role spans the entire research pipeline – from processing spatio-spectral-temporal UAV imagery to model development, algorithm validation and deployment, including contributions to a QGIS forest
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algorithms for robotic manipulators, robotic navigation, computer vision, control algorithms, and sensor fusion. You will identify technology limitations and deficiencies in existing autonomous frameworks and
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will work closely with interdisciplinary researchers and engineers to develop novel AI algorithms, publish in top-tier venues, and translate research innovations into real-world sustainability solutions
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implementation novel machine learning and large language model (LLM) algorithms for Green AI applications. Support the research of efficient AI techniques, including model optimization, parameter-efficient fine
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, high-performance scientific computing, tensor methods, and scalable algorithms. Optimization: continuous and discrete optimization, computational optimization, inverse problems, and optimization methods
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Research Infrastructure? No Offer Description The objective is to develop advanced algorithms for AI-enabled semantic and robot-control-aware communication with a particular focus on the management and
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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