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Field
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intersection of applied mathematics, computational science, and high-performance computing. The successful candidate will help develop advanced scientific computing methods and deploy them on state-of-the-art
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computational fluid dynamics, quantum computing and high-performance scientific computing, and to engage with researchers from both academia and industry. You will have substantial scientific independence
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publicly available datasets to interpret results in a robust biological context Ensure reproducibility, data management, and documentation of computational workflows in high-performance computing
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do this, the postdoctoral researcher will combine machine learning, molecular dynamics simulations and high performance computing (Isambard AI). Applicants must have a PhD in an appropriate area of
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Natural Science and the College of Engineering. CMSE centers around computational approaches, encompassing algorithm development, high-performance computing, scientific modeling, and data science
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experience is considered an advantage: Antimicrobial resistance research Metagenomics, microbial genomics, or bioinformatics Statistical programming in R or Python High-performance computing environments
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learning, deep learning tools, especially with application in drug discovery. Experience with high performance computing environment (HPC) / cluster job submission. Knowledge of statistical methods
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applications for a POSTDOCTORAL RESEARCHER in Quantum Computing Middleware and Applications . The quantum software group at the University of Helsinki consists of close to ten researchers looking at
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applications for a POSTDOCTORAL RESEARCHER in Quantum Computing Middleware and Applications . The quantum software group at the University of Helsinki consists of close to ten researchers looking at
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, high-performance computing, distributed computing, or large-scale workflow management. Experience developing reconstruction, simulation, or detector calibration software. Familiarity with modern machine