Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
be the state estimation of the robotic system from external cameras. Familiarity with existing methods from these domains, such as Deep Learning, Quality-Diversity algorithms, reinforcement learning
-
be the state estimation of the robotic system from external cameras. Familiarity with existing methods from these domains, such as Deep Learning, Quality-Diversity algorithms, reinforcement learning
-
physical models. However, to achieve reliable results choosing the right methodology and training strategy is a large scientific challenge. Your job In this project, we aim to apply deep learning techniques
-
/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
-
, concentration and functional inequalities • Mathematical aspects of machine learning and deep neural networks • Free Probability aspects of Quantum Information Theory. While excellent candidates with other
-
exceptional postdoctoral research fellows interested in developing deep learning and computational methods for pathology image analysis, multimodal data integration, and other medical modalities (e.g
-
experience in deep learning frameworks (TensorFlow/PyTorch) Experience with large-scale genomic/proteomic datasets and machine learning applied to biological sequences Knowledge of phylogenetics, protein
-
laser processing and to bring your ideas in AI/ML to the technology level. You have a solid background in programming (deep learning, reinforcement learning, etc.), electronics, high-speed data
-
projects utilizing machine learning, deep learning, and generative AI to solve business and healthcare problems have been undertaken at the Insight Lab. For more details, please refer to: https
-
processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large