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Field
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new code via
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staff position within a Research Infrastructure? No Offer Description Are you excited about causal inference, real-world data, and methodological innovation? Join us to explore how the integration
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studying k-space (Fourier domain of the image in which the acquisition is performed) samples from over the entire time series, a neural-implicit representation can infer what the full k-space should look
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to avoid sources of bias such as the target trial approach (www.bips-institut.de/en/research/cross-departmental-working-groups/working-group-gepard-target-trials-for-causal-inference-gettcausal.html ) and
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statistical inference. More specifically the recruited PhD student will consider variational inference approaches for GEA and stochastic optimization to speed up the inference, with the objective of scaling up
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is an AI-based technique that supports imitation of the preferred system behaviour by using its behavioural history. It helps in the inference of the reward values by taking the observed history
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), computation takes place only when an event occurs. Beyond reducing the amount of incoming data to process, event-based computing requires fewer operations per second during the inference phase compared
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framework will be used with advanced causal inference methods – including inverse probability weighting to construct a valid comparison group. The analysis will use the potential outcomes approach to address
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 2 months ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially