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scientific publications at major international peer-reviewed venues of core machine learning research. Strong scientific programming skills demonstrated by contributions to public code repositories or released
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Copenhagen area. The group develops the GPAW electronic structure code, the ASE Python library, and the TaskBlaster workflow framework. Substantial computational resources are available for the project through
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Institute for the Green Transition (BRIGHT) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally changed the scope
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of codes/models simulating the nucleation and propagation of stress corrosion cracking in samples under low cycle fatigue conditions, as well as models for linking the microstructure from the AM process to
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, Medicine, Pharmacy, Epidemiology, or a related discipline • Strong interest in epidemiological methods, data analysis, and coding (e.g., R, Stata, or similar) • Interest in women’s health, fertility