11 parallel-computing-numerical-methods-"Multiple" Postgraduate positions at Forschungszentrum Jülich
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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding
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related field Strong background in numerical methods and machine learning Proficiency in at least one programming language (Python, Julia, C++, …) Good analytical skills Good organizational skills and
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. Thus neuronal experimental data are to be analyzed for both aspects by PCA analysis and statistical multivariate methods to extract spatio-temporal spike patterns. Finally both results will be linked and
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Your Job: The PhD position is offered in the context of the HDS-LEE graduate school. We are looking for a highly motivated PhD candidate to join our world-leading research program in Earth System
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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method implemented into the EURAD-IM. In atmospheric chemistry modeling, the 4D-var method is a powerful tool to assess the state of the atmosphere and the corresponding emissions that are in compliance
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Your Job: Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell
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international conferences to present your own work, and learn about state-of-the-art machine learning and computer vision methods and their applications Your Profile: Excellent Master’s degree in engineering
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Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis. You will