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FieldBiological sciencesEducation LevelPhD or equivalent Specific Requirements PhD in Physics, Computational Biology, Bioinformatics, or equivalent. Knowledge of biophysics, statistical physics, machine learning
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an opportunity for renewal to perform research using artificial intelligence (AI) and machine learning (ML) with a focus on large language models (LLMs) and foundation models (FMs) relevant to electric power
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on power system dynamics and control under high inverter-based resources (IBRs). * Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation
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experiments for investigating the neural mechanisms underlying habitual behaviours and learning adaptation to uncertainty. You will use fMRI and neurostimulatory techniques (ultrasound neurostimulation and/or
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, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
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conferences in machine learning, statistics, and communications. Presenting research findings at project meetings, workshops, and international conferences. Supporting the supervision of PhD students and
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to model them through computer simulations is highly valued. · Knowledge of classical molecular dynamics, including Machine Learning Interatomic Potentials. · Other research experience will be considered
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 4 days ago
, the relation between human cognition and machine learning, and others. The position is offered for three years. The starting date is, in principle, flexible, while we aim to get started as soon as possible
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weak gravitational lensing, galaxy clusters, or large-scale structure. Experience with cosmological simulations and machine learning is highly desirable. Postdoctoral associate in exoplanet atmospheres
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About the role We invite applications for a Postdoctoral Research Assistant to be part of a new research project ‘Innate and Learned Proficiencies in Facial Age Estimation’. The project is funded by