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-engineering-and-automation/nonlinear-systems-and-control ) at Aalto University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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The Faculty of Science, Leiden Institute of Advanced Computer Science,is looking for a: PhD Candidate Human-Centered Interpretable Machine Learning (1.0fte) Project description In recent years
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Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science,is looking for a: PhD Candidate Human-Centered Interpretable Machine Learning (1.0fte) Project description In recent
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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of the) [map ] Subject Area: Mathematical Machine Learning Appl Deadline: 2025/10/13 11:59PM (posted 2025/09/16, listed until 2025/10/13) Position Description: Apply Position Description Join Us! Are you
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 1 month ago
Offer Description Funding: 36 months, CIFRE (https://www.anrt.asso.fr/fr/le-dispositif-cifre-7844 ) Starting date: November / December 2025 Keywords: Physically informed machine learning, Industrial
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of Information Security and Communication Technology has a vacancy for 1 PhD Research Fellow in Privacy Preserving Machine Learning. The successful candidate will be offered a 3-year position. Are you motivated
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with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation