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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 days ago
also opens perspectives for applying and extending continuous Bayesian networks and bandit-based experimental design approaches to agricultural systems. Because of the computational demands of crop
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& Partnerships (NSF-TIP) directorate. More information on the project is available at: https://industriesofideas.ai/ . Term-limited: This is a term-limited position for two years, with the possibility of renewal
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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Bayesian Index Tracking: optimisation by sampling School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Kostas Triantafyllopoulos, Dr Dimitrios Roxanas Application
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and neural network methods will be used to transfer diagnostic capability between structures in a population. Bayesian approaches will also be emphasised. The Research Associate will take a leading role
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | about 1 month ago
dynamics in health and pathology; (2) in silico models, including Bayesian models, neural mass models and spiking neural networks; (3) in vitro neuronal network measurements. Our aim is to innovate in
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learning models such as Bayesian optimization, neural networks, random forests. A high proficiency in spoken and written English. Excellent communication and interpersonal skills. You are expected to learn