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programming in Python and Bash and working in HPC environments using workflow managers such as Snakemake or Nextflow. Experience in the analysis of pancreatic islet or pancreas single-cell genomic datasets is
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and HPC/GPU systems, with version control (git) and reproducible workflows (conda or containers, Snakemake or Nextflow).•Able to work independently as well as within an interdisciplinary, international
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supercomputer hardware. The research work will be informed by collaborations with the scientific computing team that manages the local HPC resources at NTNU, and Uninett Sigma2, which manages both the Norwegian
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Civil Engineering, Mechanical, Electrical, or a closely related field. Demonstrated expertise in ESM and IAM. Experience with High Performance Computing (HPC) and large-scale dataset analysis. Strong
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and optimization problems at unprecedented speed and scale. While high-performance computing (HPC) has become the backbone of large-scale power system simulation, emerging quantum computing technologies
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, parabolic equations, ray-tracing. Skills: excellent computational skills: Python, Fortran, HPC. Language skills: Fluent in English, Spanish is not required but advantageous. Specific Requirements We
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational
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-learning frameworks, such as PyTorch, and high-performance computing (HPC) environments. Knowledge of molecular and cellular biology, systems biology, or precision medicine. Finally, a letter of intent
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for biomedical research Electronic Health Record (EHR) analytics and clinical data integration Biomedical image analysis and quantitative microscopy High-performance computing (HPC) and scalable AI pipelines
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Ability to curate and integrate large scale biomedical data Experience with workflow management and HPC environments Interest in RNA biology, alternative splicing and computational method development Strong