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science, or a related field. Strong background in quantitative methods and statistical analysis. Experience with computational tools for large-scale data analysis (e.g., Python, R, SQL). Familiarity with
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. Preferred Qualifications Knowledge of aging-in-place, accessibility, or universal design. Experience with AR/VR tools, programming/coding (Python, R, Unity, or JavaScript), or community-engaged research
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Python, Julia or C++ Knowledge of modern deep learning frameworks (e.g. pyTorch) Knowledge of collaborative software development tools (e.g. Version control: Git) Experience working in Linux shell/cluster
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data, quality assessment/filtering, alignment and variant detection. Experience with long-read (PacBio/ONT) NGS sequencing, genome assembly and annotation Strong competence in programming (shell/python/R
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(e.g. Python, MATLAB or equivalents); Interest in applied thermodynamics, numerical simulation and sustainable energy systems. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7274-SILLAS
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | 18 days ago
, or publications. Programming/engineering expertise. Proficient in Python and practical with a deep-learning framework (PyTorch or TensorFlow). Comfortable writing clean, reproducible code and using version control
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-motivation and interest to learn new skills Great to have: Experience programming in Python, Julia, or C/C++ Experience with Mathematica Experience with finite element methods, agent-based simulations, and/or
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Qualifications Education: ABD status by start date. PhD by start date in a field relevant to the research being conducted. PhD after one year of employment. Technical Skills or Knowledge: Proficiency in Python
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. Your qualifications MSc degree (or equivalent) in physics Knowledge of plasma physics is a plus Experience in programming languages (e.g. Python, C++) Proficiency in English, both written and spoken We
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differential testing) We focus on techniques that apply to real-world software systems. E.g., in the past, we have developed techniques that find and fix bugs in widely used Python, Java, C/C++, and JavaScript