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for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI
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and illegal logging detection. Working at the intersection of computer vision, deep learning, geospatial analysis and remote sensing, the postholder will collaborate closely with academic and
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implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Utilize PyTorch to train and fine
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. The research project focuses on the design, development and validation of Artificial Intelligence and Machine/Deep Learning models applied to healthcare, with particular reference to computer vision applied
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 5 days ago
: tyrex.inria.fr Relational learning has recently gained renewed momentum through the development of end-to-end deep learning approaches over relational databases. In this setting, relational tables are typically
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both traditional statistical machine learning (e.g., tree-based ensembles, regression) and modern deep learning architectures (e.g., Transformers, sequence models, embeddings). Experience working with
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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advanced machine learning feature detection to enable evolving subsea scenes to be robustly aligned across repeat surveys. You will develop probabilistic models to detect subtle changes under noise and
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a candidate with deep insight and interest in investigating the interaction between
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and remote sensing imagery for ecosystem monitoring. Develop machine/deep learning-based workflows to interpret ecosystem disturbance. Synthesize model simulations and multi-source observations