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Field
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, the following elements will be positively evaluated: Previous experience in fully data-driven weather forecasting; Previous experience with downscaling climate data; Basic knowledge of HPC systems (e.g., SLURM
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(HPC): Experience with parallel computing (MPI, OpenMP, CUDA/HIP) or running workflows on supercomputing clusters. Software Engineering: Knowledge of version control (Git), containerization (Docker
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formats as appropriate). Analyzes and integrates multi-modal genomic datasets using computational approaches (with access to robust HPC resources). Evaluates data to plan subsequent stages of projects and
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in programming, ideally with experience in languages commonly used in computational biology (e.g. Python, C). Experience with HPC, workflow managers (e.g. Snakemake, Nextflow), and containerization
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multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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channels for LWFA. - Run and combine plasma simulation codes on national HPC platforms. - Develop multi-physics workflows by coupling different simulation tools. - Analyze and interpret simulation results
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Graph neural networks Generative models (VAEs, diffusion models) Multi-modal learning Knowledge of bioinformatics tools and data formats (FASTQ, BAM, VCF, H5AD, AnnData, Seurat, etc.). Experience with HPC
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent research and publish in peer-reviewed journals Strong written and verbal
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(HPC) environments and large-scale data management. Experience with version control (e.g., Git) and collaborative software development practices. Experience with real-time analysis and instrument control