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Engineering, or a related field Strong programming skills in Python and SQL; experience with C/C++ Experience in data modelling and dimensional modelling Experience with CI/CD workflows for data and software
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of Career Development is committed to inclusive excellence, and we encourage applicants from distinct backgrounds. Learn more about our office, here: https://www.american.edu/sis/career/. Applicants
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services can be found at: https://www.uu.se/forskning/snpseq and https://ngisweden.scilifelab.se/ We are proud to deliver high-quality data and are accredited by SWEDAC as a testing laboratory under the ISO
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures Knowledge in the field of ML security is desirable. Good Python skills, especially with
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skills. Is confident using digital learning tools such as Python, SAS, Stata or similar. Holds (or will soon complete) a doctorate in Finance or a closely related field. Enjoys contributing to the wider
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. Practical experience applying machine learning or deep learning methods to biological data. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM
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permanent and temporary grasslands. These results will clarify the potential contribution of grassland ecosystems to achieving France's 2050 carbon neutrality goal. Where to apply Website https
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to the development of the project. Participation in the collection, organization and maintenance of databases and technical information generated by the working groups. Where to apply Website https://www.iisaragon.es
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of machine learning or quantum computing Programming skills in Python and/or C/C++ Experience with scientific software tools and numerical libraries Familiarity with Linux-based computing environments Ability
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, including branching strategies, pull requests, and documentation-as-code. Ensure all analytical scripts (SQL, R, Python) are versioned, audited, and recoverable. Implement CI/CD (Continuous Integration