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Field
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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of precipitation and temperature over Morocco. Key Responsibilities: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation
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and conferences. Proven experience in design and implementation of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas
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- Planeamento de tratamento biológico robusto do cancro pancreático em radioterapia”, “2024.14662.PEX”, “DOI: https://doi.org/10.54499/2024.14662.PEX ”, funded by the Fundação para a Ciência e a Tecnologia, I.P
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include: Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines. Build reproducible research pipelines and maintain reliable
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an emphasis on technology, data science and the humanities. For more details, please view https://www.ntu.edu.sg/medicine . We are looking for a Research Fellow to conduct AI for medicine research. The role
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exam. Desired qualifications: Experience with data simulation, clustering algorithms, benchmarking, model selection and evaluation workflows is an advantage Language requirement: Good oral and written
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 days ago
expected to develop and run workshops to introduce your work to end users. For further detail on the Lanfear Lab, our ideals and goals please visit our webpage: http://biology.anu.edu.au/research/labs
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, particularly Python; (ii) use of parameter optimization algorithms, particularly PEST and PEST++; (iii) remote sensing applied to the water cycle; and (iv) application of machine learning techniques to spatio