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science, computational biology, engineering, statistics, mathematics.). Experience and interest in prediction modelling Proficient in statistical software and programming languages and familiarity with relevant libraries
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fields • Prior experience in analysing EEG data. • Possess strong programming skills (mostly Python) and familiar with statistical methods. • Have good communication and writing skills
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programme designated to attract and empower the world’s brightest early-career researchers. This fellowship supports outstanding scientists who harness Artificial Intelligence (AI) to accelerate breakthroughs
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) Programme studies the causes and treatments of cancer and related diseases. The CSCB research groups have diverse programmes in both basic cancer biology and clinical-translational studies, with a special
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framework such as Tensorflow, Pytorch, MXNet and Programming Languages such as Python, Matlab, R and/or C/C++. Demonstrated project experience related to causal inference will be an advantage. Good written
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in signal representation/processing, esp for scent signals. Prior research experience and track record in signal detection, machine learning and deep learning. Prior programming experience in state
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in mathematical modelling methods used to analyse infectious diseases • Strong programming skills, ideally with experience in R/R packages and GitHub as a collaborative coding environment • An ability
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an intellectually stimulating, globally diverse scientific community. Key Responsibilities • Designing and managing a programme of research to meet agreed objectives. • Working closely with experimental
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an intellectually stimulating, globally diverse scientific community. Key Responsibilities • Designing and managing a programme of research to meet agreed objectives. • Working closely with experimental
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, or a related field. Expertise in deep learning, multimodal LLMs, and Vision-Language-Action models. Strong programming skills in Python, with significant experience in PyTorch. Hands-on experience with