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: Experience materials design and materials selection Experience in chemical reaction development Expertise in complementary methods such as ICP-MS, XRD, XPS, SEM, TEM, EDX Scripting in Matlab, Python
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mechanical/electrical/biomedical/human factors engineering or a related discipline Strong programming skills (e.g., Python, R) Experience with data processing and analysis Knowledge of statistics, or a strong
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engineering, or another related field Strong knowledge of Machine Learning theory and methods, and related Deep Learning approaches Excellent knowledge of programming in Python and scientific libraries used
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for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required (Python/R, ML/stats
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communication skills in written and spoken English. Proficiency in programming with high-level languages like Python. The following will strengthen your application: Familiarity with open quantum systems
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beamline Publish results in scientific journals and present findings at international conferences Where to apply Website https://apply.refline.ch/673278/3854/EL6dzSlLCLf7qHjFYjOSmL8NTV0nuikWIOXeIbXpRu
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languages such as R, Python, and/or SQL. Strong attention to detail, highly organized, timely, and responsive. Excellent interpersonal, written, presentation, and verbal communication skills. Experience
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 13 days ago
programming skills and background in AI; Proficiency in R and/or Python, especially regarding the use of libraries specific to bioinformatic analysis (e.g., DESeq2/pyDESEQ2, clusterProfiler/GSEApy, Seurat
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 26 days ago
, France, industries, etc). Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09879 Requirements Skills/Qualifications Good skills in Python (Pytorch). Ideally, prior experience with
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Python, PyTorch, and Linux/command line Familiarity with LLM in-context learning and prompt engineering Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented