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and generative protein design (e.g. AlphaFold, OpenFold, Boltz, Chai). Develop robust, reproducible and reusable Python code for model training, inference, and large‑scale computational experiments. Run
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architectures (e.g., convolutional neural networks or transformers); deep specialization is not required. Exposure to Generative AI concepts and large language models (LLMs) is a plus. Proficiency in Python
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genomics data, writing Python code for data analysis, and a downstream R pipeline for post-processing data using standard Bioinformatics libraries from Bioconductor. There will be opportunities
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choose from several health coverage options offered by The Texas A&M University System for themselves and their families, as well as numerous other benefit programs. https://www.tamus.edu/business/benefits
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their results in the context of the clients. Analyses will be conducted with several software packages for statistical data analysis (possibly including R, SAS, Python, …). The new colleague may acquire new
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, deformation mechanisms and mechanical performance, ultimately enabling more efficient design and optimization of advanced structural materials. [1] https://www.pepr-diadem.fr/projet/ammetis-2/ [2] https
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for the design and optimization of advanced structural materials. [1] https://www.pepr-diadem.fr/projet/ammetis-2/ [2] https://www.pepr-diadem.fr/ Where to apply E-mail mohamed.jebahi@ensam.eu Requirements
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or equivalent Skills/Qualifications Conocimientos de programación (Python). Empleo de herramientas de modelización numérica geotécnica (FLAC, PFC). Specific Requirements Conocimientos en Ingeniería Civil
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/Qualifications Experience with molecular simulations (LAMMPS, GROMACS or equivalent) and/or electrostatics simulations (APBS or equivalent). Strong programming skills (Python, FORTRAN, C, or similar). Experience
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PID controllers; 8) proficiency in programming languages: C, C++, Python; 9) experience in conducting teaching activities in both Polish and English will be an additional advantage. Required documents