16 python-"Multiple"-"NTNU---Norwegian-University-of-Science-and-Technology" positions in Switzerland
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advanced deep learning models: Design and implement a multi-branch neural network capable of integrating multiple data modalities into a unified representation. Implement a multi-task learning framework
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scalable, robust, and reproducible analysis pipelines (Python/R; Snakemake/Nextflow and configuration frameworks such as Hydra preferred) for novel experimental methods, including in vivo Perturb-seq
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collaborative approach involving multiple doctoral and postdoctoral researchers on material surface development, in vivo small-animal studies, in vitro organotypic bone models and in vivo large animal. The
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characterisation techniques is beneficial, but not required; Experience in at least one programming language for scientific computing (C/C++, Matlab, Fortran, Python, Julia, ...); Good communication skills and
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modelling; Knowledge of spectroscopy is beneficial, but not required; Experience in at least one programming language for scientific computing (C/C++, Matlab, Fortran, Python, Julia, ...); Good communication
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the clinical translation of REE-free Mg-based osteosynthesis systems. Project team and setup: Within this SNSF-funded project, we will follow a multidisciplinary collaborative approach involving multiple
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(target gene selection, power analyses, guide-library design, readout selection). Build, maintain, and document reproducible analysis pipelines (Python/R; Snakemake/Nextflow preferred) for novel
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international summer schools and present your research at workshops and scientific conferences. Publish multiple high-impact publications and collaborate with partner groups at the University of Cambridge (U.K
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mechanical and electronic workshops. Have the opportunity to attend international summer schools and present your research at workshops and scientific conferences. Publish multiple high-impact publications and
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(target gene selection, power analyses, guide-library design, readout selection). Build, maintain, and document reproducible analysis pipelines (Python/R; Snakemake/Nextflow preferred) for novel