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bioinformatics tools, pipelines, and statistical methods for the analysis of large-scale genomic and transcriptomic datasets ('big data'), with hands-on experience in high-performance computing (HPC) environments
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benchmarking of large language models (LLMs). The research profile of the group is heavily machine-learning oriented and the group has access to excellent HPC infrastructure. For more information about LTG
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computing (HPC) for large-scale data analysis. Experience with seismic tomography, full-waveform inversion, or other advanced imaging techniques. Familiarity with modern data processing workflows and software
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: Experience in analyses and interpretation of clinical data in combination with microbiome or other -omics data. Experience with use of HPC clusters and workflow management tools (Snakemake, Nextflow). Strong
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members have access to large-scale computational resources through national and European HPC allocations, and this doctoral fellowship is expected to have a strong experimental component. Candidate
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defense are eligible for appointment. Programming skills in GAMS and Python. Experience with HPC. Experience with