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Field
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Your Job: In this Master’s thesis, you will investigate the impact of different programming algorithms on the stability of resistance states using a sophisticated 3D Kinetic Monte Carlo (KMC) model
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
on particulate and dissolved organic matter from hyperspectral absorption data sampled at Arctic expeditions at AWI’s Hausgarten (Fram Strait) in the last 10 years by optimizing established algorithms from
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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aspects across a wide range of fields - from biomechanics and geophysics to polymer-fluid coupling. Further areas of interest include numerical algorithms for high-dimensional problems, classical (mainly
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. Requirements: • Bachelor's degree in computer science or equivalent knowledge Desirable: • Knowledge and practical experience in areas such as algorithms, data structures, software engineering, artificial
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software
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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning