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from chip. Characterise and optimise the algorithm for signal data processing for real-time cell analysis. Develop a user-interface platform for end-user testing of clinical samples. Job Requirements
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the neural mechanisms underlying goal switching and behavioural strategy selection, linking algorithmic theories of behaviour to defined microcircuits and pathways. The position will employ a multidisciplinary
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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estimations in humanitarian and public health contexts by developing reproducible, multilingual workflows for social media analysis, building data pipelines in R/Python, and creating open-source tools for text
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progress. Ability and willingness to work some flexible hours. Extensive experience in large-scale pre-training of large language model. Experienced in developing machine learning algorithms and large
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Responsibilities: Design and implement advanced AI/ML models for healthcare applications, including predictive analytics and generative AI solutions. Develop and validate digital phenotyping algorithms using
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designing and improving general algorithms for algebraic cryptanalysis, or developing concrete attacks against proposed ciphers. This PhD position is an opportunity to explore and shape your own research
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University. Key Responsibilities: Conduct research on methods and approaches to support air traffic management studies and applications. Develop, test, and evaluate analytical models, algorithms, and tools
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protocols. Specific research areas will be discussed with the successful applicant, but may include designing and improving general algorithms for algebraic cryptanalysis, or developing concrete attacks
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manage research datasets, including development of analytic workflows, REDCap data collection tools, algorithm development, and validation of NLP pipelines · lead the development of scholarly outputs