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Field
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algorithms and experimental validation platforms for high-precision, high-speed and robust three-dimensional sensing. Key Responsibilities: Conduct research on structured-light three-dimensional imaging
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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic
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, physical AI, and spatial AI. The RF will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision Group’s long
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required for discovering genetic (e.g., SNP, CNV) and epigenetic (e.g., DNA methylation) variations to support eco-evolutionary studies, QTL mapping, or other applications of genomic sequence variation
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lead the design, statistical optimisation and validation of assays for clinically relevant bladder cancer targets. Their central objective will be to develop an algorithmic workflow to detect new target
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Details Title Postdoctoral Fellow in Epigenomics and Human Biology School Faculty of Arts and Sciences Department/Area Human Evolutionary Biology Position Description We seek a postdoctoral research
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rapid, targeted gene evolution while preserving host viability, enabling us to study fundamental evolutionary processes and develop new molecular solutions for problems in the areas of health and
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-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel algorithms for: Fine-grained video understanding Concept learning Temporal
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. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic modeling
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optimisation, algorithm design and high-performance computing, with application to airport innovation. Successful candidates will join an active group of Principal Investigators and researchers to work within