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, Computer Science, or a related field. At least two years of postdoctoral or equivalent research experience, with a strong record of peer-reviewed publications. Strong programming and computational skills in Python
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participating in research projects (20%); c) Experience in programming in Python and related languages (20%). 10. Selection Jury Composition: Ana Isabel Pereira José Lima Inês Sena 11. Method of publication
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, protein purification, and/or machine learning is a clear plus. • Experience in data analysis and coding (preferably Python) • A systematic, independent working style and ability to work in a collaborative
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that candidates possess expertise in some (but not all, or even most) of the following areas: A strong mathematical background Ability to program in MATLAB, Python, or a similar scientific programming language
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characterization is an advantage. Experience with quantitative data analysis and programming (e.g. Python or MATLAB) is an asset. A self-motivated and organized working style, with the ability to work independently
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quantitative field. Good scientific programming skills, particularly in Python, are required. Experience with atmospheric dynamics, numerical modelling, machine learning, or large meteorological datasets would
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or equivalent research experience, with a strong record of peer-reviewed publications. Strong programming and computational skills in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience
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PhD. Be able to commence the Program in the year of the offer. The ideal PhD candidate will have: A strong background in machine learning, deep learning, and software programming Proficiency in Python
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developing profile and an understanding of relevant methods and techniques. Strong numerical and computational skills, plus proficiency in at least one of: Python, MATLAB, or C++, particularly for data
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a nanoparticle printer, with systematic control of composition and deposition conditions. Characterize samples with micro-XRF composition mapping and SEM, and develop reproducible Python pipelines