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Field
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Informal enquiries can be made to Dr Hazel Wilkinson, Deputy Director IDAI, email
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:………..………………………………………………………………………………………………………………………………………… Management, with particular focus on the intersection of: Machine Learning Causal Inference Applied Field Experimentation Scientific Areas: Management, Economics, Information Systems, Computer Science, Data
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- Life Sciences: Genomics, precision medicine, bioengineering, and health data science - AI and Digital: Machine learning, robotics, digital health, and cybersecurity - Defence and Advanced Manufacturing
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advanced pharmacy practice and a desire to acquire extensive experience in ambulatory care practice and research. The well-rounded training and experience gained through this program equips graduates to be
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advanced pharmacy practice and a desire to acquire extensive experience in ambulatory care practice and research. The well-rounded training and experience gained through this program equips graduates to be
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Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven