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algorithms for analysis of large image datasets. Experience with parallel computing, high-performance computing, distributed computing, and/or cloud-based computational workflows. Experience with large-scale
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approaches to study RNA turnover or with massively parallel reporter assays (MPRAs) will be beneficial. Must Have Bioinformatics experience in the analysis of (RNA) sequencing data Experience with common lab
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with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows. Demonstrated technical
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focusing on: Next-generation energy storage systems Power converter design for Power-to-X (PtX) solutions Microgrid applications Quantum computing in power systems And other emerging technologies in
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, and development of tools suitable for high-performance computing environments. Experience with parallel computing and workload management systems such as SLURM is highly desirable. Model Calibration
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, ecology, microbiology, engineering, bioinformatics, data mining, parallel programming, supercomputing, or cloud computing. Application Instructions How To Apply Interested individuals should send
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candidates should have a strong background in computer science, parallel computing, compilers, performance optimisation, and high-performance computer systems. Excellent knowledge of C and C++ is
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, engineering, bioinformatics, computer science, mathematics, statistics, data mining, parallel programming, supercomputing, or cloud computing . Application Instructions How To Apply Interested individuals
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and physical processes relevant to ocean circulation and dynamics. Experience with high-performance computing, parallel numerical models, large scientific datasets, scientific programming, and the
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learning, high-performance and parallel computing, or scientific simulation; Effective oral and written communication skills; Ability to work well independently as well as in a collaborative team