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Qualifications The ideal candidate will have expertise in one or more of the following research areas, without being an exhaustive list: Proven track-record within synthetic biology, ideally within yeast
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datasets. Proficient in Python and the various numerical packages (e.g. NumPy, Pandas, etc) Ability to work both independently and as a part of a team. Excellent communication and writing skills in English
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processes contributing to sea level change; b) experience with ocean and/or earth system modeling; c) experience with Python and scientific data analysis. Candidates must have a Ph.D. or expect to complete a
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nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified
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to the field of research, especially those listed in the Science Citation Index, in relation to the duration of the candidate’s scientific career. Of special importance are the first-authored papers by
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experience. The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list
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performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right
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-binding modeling of materials, as evidenced in application materials.. 2. Previous work experience that required Python programming skills, as evidenced in application materials. 3. Previous experience
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. Ability to handle large volumes of data and familiarity with household surveys are required, alongside solid data analysis skills (R, Stata, Python, etc.) and familiarity with academic writing and
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include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory